Ethical principles for the use of AI in cybersecurity | IGF 2023 WS #33
Event report
Speakers and Moderators
Speakers
- Amal El Fallah-Seghrouchni, Executive President, Moroccan International Center for Artificial Intelligence
- Anastasiya Kazakova, Cyber Diplomacy Knowledge Fellow, DiploFoundation
- Dennis-Kenji Kipker, Expert in Cybersecurity Law, University of Bremen
- Jochen Michels, Head of Public Affairs Europe, Kaspersky, Europe
- Noushin Shabab, Senior Security Researcher, Global Research and Analysis, Kaspersky, Australia
Moderators
- Genie Sugene Gan, Head of Government Affairs, APAC, Kaspersky
Table of contents
Disclaimer: This is not an official record of the IGF session. The DiploAI system automatically generates these resources from the audiovisual recording. Resources are presented in their original format, as provided by the AI (e.g. including any spelling mistakes). The accuracy of these resources cannot be guaranteed. The official record of the session can be found on the IGF's official website.
Knowledge Graph of Debate
Session report
Martin Boteman
The discussion delves into the significance of identity in the realm of security and the crucial role that AI can play in safeguarding identities. It is acknowledged that with the advancement of AI, data has become more frequently personally identifiable than ever before, leading to a need to address the complex relationship between identity and privacy.
One argument put forward is that security will require identity. The increasing personal identifiability of data, facilitated by AI, has made it imperative to establish and protect individual identities for the sake of security. This argument highlights the evolving nature of security in the digital age and the need to adapt to these changes.
On the other hand, a positive stance is taken towards the potential of AI in enhancing security with the identity factor. It is suggested that AI can aid in securing identities by leveraging its capabilities. The specifics of how AI can contribute to this aspect are not explicitly mentioned, but it is implied that AI can play a role in ensuring the authenticity and integrity of identities.
Furthermore, the discussion recognises the necessity to address the dichotomy between identity and privacy. While identity is essential for security purposes, safeguarding privacy is equally important. This creates a challenge in finding a balance between the two. The analysis raises the question of how to deal with this dichotomy in future endeavours, emphasizing the need for a thoughtful and nuanced approach.
Legal measures are acknowledged as an important consideration in the context of AI. However, it is argued that relying solely on legal frameworks is not enough. This underlines the complexity of regulating AI and the urgent need for additional measures to ensure the responsible and ethical use of the technology. The mention of the Algorithmic Accountability Act in the USA and the European Union's AI Act serves to highlight the efforts being made to address these concerns.
Overall, there is a positive sentiment regarding the potential of AI in enhancing security with the identity factor. The discussion reinforces the significance of ethical principles such as security by design and privacy by design when implementing AI solutions. It asserts that taking responsibility for AI and incorporating these principles into its development and deployment is essential.
It is worth noting that the expanded summary provides a comprehensive overview of the main points discussed. However, more specific evidence or examples supporting these arguments could have further strengthened the analysis. Nonetheless, the analysis highlights the intersection of identity, privacy, AI, and security and emphasizes the need for responsible and balanced approaches in this rapidly evolving landscape.
Amal El Fallah-Seghrouchini, Executive President, Moroccan International Center for Artificial Intelligence
Artificial Intelligence (AI) has emerged as a powerful tool in the field of cybersecurity, with the potential to enhance and transform existing systems. By leveraging AI, common cybersecurity tasks can be automated, allowing for faster and more efficient detection and response to threats. AI can also analyze and identify potential threats in large datasets, enabling cybersecurity professionals to stay one step ahead of cybercriminals.
The importance of AI in cybersecurity is further highlighted by its recognition as a national security priority. Organizations such as the National Science Foundation (NSF), National Science and Technology Council (NSTC), and National Aeronautics and Space Administration (NASA) have emphasized the significance of AI in maintaining the security of nations. This recognition demonstrates the growing global awareness of the role that AI can play in safeguarding critical infrastructure and sensitive data.
However, the use of AI in cybersecurity also raises concerns about the vulnerability of AI systems. Adversarial machine learning techniques can be deployed to attack AI systems, potentially compromising their effectiveness. It is crucial to regulate the use of AI in cybersecurity to mitigate these vulnerabilities and ensure the reliability and security of these systems.
Furthermore, AI is not only a tool for defending against cyber threats but can also be used to create new kinds of attacks. For example, AI-powered systems can be utilized for phishing, cyber extortion, and automated interactive attacks. The potential for AI to be used maliciously highlights the need for robust ethical and regulatory considerations in the development and deployment of AI systems in the cybersecurity domain.
Ethical and regulatory considerations are necessary to strike a balance between the power of AI and human control. Complete delegation of control to AI in cybersecurity is not recommended, as human oversight and decision-making are essential. Frameworks should be established to ensure the ethical use of AI and to address concerns related to privacy, data governance, and individual rights.
Initiatives aimed at differentiating between identifier and identity are being pursued to strengthen security and privacy measures. By avoiding the use of a unique identifier for individuals and instead associating sectorial identifiers with identity through trusted third-party certification, the risk of data breaches and unauthorized access is reduced.
In addition to data protection, ethics in AI extend to considerations of dignity and human rights. It is essential to incorporate these ethical principles into the design and implementation of AI systems. Furthermore, informed consent and user awareness are crucial in ensuring that individuals understand the implications and potential risks associated with using generative AI systems.
Preserving dignity and human rights should be a priority in all systems, including those powered by AI. This encompasses a continuous debate and discussion in which the principles of ethics play a central role. Educating the population and working towards informed consent are important steps in achieving a balance between the benefits and potential harms of AI.
Accountability, privacy, and data protection are recognized as tools towards ensuring ethical practices. These principles should be integrated into the development and deployment of AI systems to safeguard individual rights and maintain public trust.
Overall, AI has the potential to revolutionize cybersecurity, but its implementation requires careful consideration of ethical, regulatory, and privacy concerns. While AI can enhance and transform the field of cybersecurity, there is a need for comprehensive regulation to address vulnerabilities. The differentiation between identifier and identity, as well as the emphasis on dignity and human rights, are important factors to consider in deploying AI systems. Promoting informed consent, user awareness, and ethical use of AI should be prioritized to maintain a secure and trustworthy digital environment.
Audience
During the discussion, the speakers delved into the implementation of ethical AI in the field of cybersecurity and raised concerns regarding its potential disadvantages when countering unethical adversarial AI. They emphasised that adversaries employing adversarial AI techniques are unlikely to consider ethical principles and may operate without any regard for the consequences of their actions.
The audience expressed apprehension about the practicality and effectiveness of using ethical AI in defending against unethical adversarial AI. They questioned whether the application of ethical AI would provide a sufficient response to the increasingly sophisticated and malicious tactics employed by adversaries. It was noted that engaging in responsive actions by deploying ethical AI to counter unethical adversarial AI might place defenders at a disadvantage, highlighting the complexity of the issue.
Given these concerns, the need for a thorough review of the application of ethical AI in response to unethical adversarial AI was acknowledged. There was specific emphasis on active cyber defence, which involves proactive measures to prevent cyber attacks and mitigate potential harm. The aim of the review is to ensure that the use of ethical AI is optimised and effectively aligned with the challenges posed by unethical adversarial AI.
These discussions revolved around the topics of Ethical AI, Adversarial AI, Cybersecurity, and Active Cyber Defence, all of which are highly relevant in today's digital landscape. The concerns raised during the discussion reflect the ongoing tension between the desire to uphold ethical principles and the practical challenges faced when countering adversaries who disregard those principles.
Furthermore, this discussion aligns with the Sustainable Development Goals (SDGs) 9 and 16, which emphasise the importance of creating resilient infrastructure, fostering innovation, promoting peaceful and inclusive societies, and ensuring access to justice for all. By addressing the ethical challenges associated with adversarial AI in cybersecurity, efforts can be made towards achieving these SDGs, as they are integral to building a secure and just digital environment.
Overall, the discussion underscored the need for careful consideration and evaluation of the application of ethical AI in response to unethical adversarial AI. Balancing the ethical dimension with the practical requirements of countering adversaries in the ever-evolving digital landscape is a complex task that warrants ongoing discussion and analysis.
Anastasiya Kazakova, Cyber Diplomacy Knowledge Fellow, DiploFoundation
Artificial Intelligence (AI) plays a crucial role in enhancing cybersecurity by improving threat detection and intelligence gathering. However, concerns have been raised regarding the autonomous nature of AI and its potential to make impactful decisions in everyday life. It is argued that AI should not operate solely autonomously, highlighting the importance of human oversight in guiding AI's decision-making processes.
A major issue faced in the field of AI is the anticipation of conflicting AI regulations being established by major markets, including the EU, US, and China. This potential fragmentation in regulations raises concerns about the limitations and hindered benefits of AI. It is important to have uniform regulations that promote the widespread use and opportunities of AI for different communities.
The challenge of defining AI universally is another issue faced by legislators. With AI evolving rapidly, it becomes increasingly difficult to encompass all technological advancements within rigid legal frameworks. Instead, the focus should be on regulating the outcomes and expectations of AI, rather than the technology itself. This flexible and outcome-driven approach allows for adaptable regulations that keep up with the dynamic nature of AI development.
In the realm of cybersecurity, the question arises of whether organizations should have the right to "hack back" in response to attacks. Most governments and industries agree that organizations should not have this right, as it can lead to escalating cyber conflicts. Instead, it is recommended that law enforcement agencies with the appropriate mandate step in and investigate cyberattacks.
The challenges faced in cyberspace are becoming increasingly sophisticated, requiring both technical and policy solutions. Addressing cyber threats necessitates identifying the nature of the threat, whether it is cyber espionage, an Advanced Persistent Threat (APT), or a complex Distributed Denial of Service (DDoS) attack. Hence, integrated approaches involving both technical expertise and policy frameworks are essential to effectively combat cyber threats.
Ethical behavior is emphasized in the field of cybersecurity. It is crucial for good actors to abide by international and national laws, even in their reactions to unethical actions. Reacting unethically to protect oneself can compromise overall security and stability. Therefore, ethical guidelines and considerations must guide actions in the cybersecurity realm.
The solution to addressing cybersecurity concerns lies in creativity and enhanced cooperation. Developing new types of response strategies and increasing collaboration between communities, vendors, and governments are vital. While international and national laws provide a foundation, innovative approaches and thinking must be utilized to develop effective responses to emerging cyber threats.
Regulations play an important role in addressing AI challenges, but they are not the sole solution. The industry can also make significant strides in enhancing AI ethics, governance, and transparency without solely relying on policymakers and regulators. Therefore, a balanced approach that combines effective regulations with industry initiatives is necessary.
Increased transparency in software and AI-based solution composition is supported. The initiative of a "software bill of materials" is seen as a positive step towards understanding the composition of software, similar to knowing the ingredients of a cake. Documenting data sources, collection methods, and processing techniques promotes responsible consumption and production.
In conclusion, AI has a significant impact on cybersecurity, but it should not operate exclusively autonomously. Addressing challenges such as conflicting regulations, defining AI, the right to "hack back," and increasing sophistication of cyber threats requires a multidimensional approach that encompasses technical expertise, policy frameworks, ethical considerations, creativity, and enhanced cooperation. Effective regulations, industry initiatives, and transparency in software composition all contribute to a more secure and stable cyberspace.
Noushin Shabab, Senior Security Researcher, Global Research and Analysis, Kaspersky
Kaspersky, a leading cybersecurity company, has harnessed the power of artificial intelligence (AI) and machine learning to strengthen cybersecurity. They have integrated machine learning techniques into their products for an extended period, resulting in significant improvements.
Transparency is paramount when using AI in cybersecurity, according to Kaspersky. To achieve this, they have implemented a global transparency initiative and established transparency centers in various countries. These centers allow stakeholders and customers to access and review their product code, fostering trust and collaboration in the cybersecurity field.
While AI and machine learning have proven effective in cybersecurity, it is crucial to protect these systems from misuse. Attackers can manipulate machine learning outcomes, posing a significant threat. Safeguards and security measures must be implemented to ensure the integrity of AI and machine learning systems.
Kaspersky believes that effective cybersecurity requires a balance between AI and human control. While machine learning algorithms are adept at analyzing complex malware, human involvement is essential for informed decision-making and responding to evolving threats. Kaspersky combines human control with machine learning to ensure comprehensive cybersecurity practices.
Respecting user privacy is another vital consideration when incorporating AI in cybersecurity. Kaspersky has implemented measures such as pseudonymization, anonymization, data minimization, and personal identifier removal to protect user privacy. By prioritizing user privacy, Kaspersky provides secure and trustworthy solutions.
Collaboration and open dialogue are emphasized by Kaspersky in the AI-enabled cybersecurity domain. They advocate for collective efforts and knowledge exchange to combat cyber threats effectively. Open dialogue promotes the sharing of insights and ideas, leading to stronger cybersecurity practices.
It is crucial to be aware of the potential misuse of AI by malicious actors. AI can facilitate more convincing social engineering attacks, like spear-phishing, which can deceive even vigilant users. However, Kaspersky highlights that advanced security solutions, incorporating machine learning, can identify and mitigate such attacks.
User awareness and education are essential to counter AI-enabled cyber threats. Kaspersky underscores the importance of educating users to understand and effectively respond to these threats. Combining advanced security solutions with user education is a recommended approach to tackle AI-enabled cyber threats.
In conclusion, Kaspersky's approach to AI-enabled cybersecurity encompasses leveraging machine learning, maintaining transparency, safeguarding systems, respecting user privacy, and promoting collaboration and user education. By adhering to these principles, Kaspersky aims to enhance cybersecurity practices and protect users from evolving threats.
Dennis Kenji Kipker, Expert in Cybersecurity Law, University of Bremen
The discussions revolve around the integration of artificial intelligence (AI) and cybersecurity. AI has already been used in the field of cybersecurity for automated anomaly detection in networks and to improve overall cybersecurity measures. The argument is made that AI and cybersecurity have been interconnected for a long time, even before the emergence of use cases like generative AI.
It is argued that special AI regulation specifically for cybersecurity is not necessary. European lawmakers are mentioned as leaders in cybersecurity legislation, using the term "state-of-the-art of technology" to define the compliance requirements for private companies and public institutions. It is mentioned that attacks using AI can be covered by existing national cyber criminal legislation, without the need for explicit AI-specific regulation. Furthermore, it is highlighted that the development and security of AI is already addressed in legislation such as the European AI Act.
The need for clear differentiation in the regulation of AI and cybersecurity is emphasized. Different scenarios need different approaches, distinguishing between cases where AI is one of several technical means and cases where AI-specific risks need to be regulated.
The privacy risks associated with AI development are also acknowledged. High-impact privacy risks can arise during the development process and need to be carefully considered and addressed.
The struggles in implementing privacy laws and detecting violations are mentioned. It is suggested that more efforts are needed to effectively enforce privacy laws and detect violations in order to protect individuals' privacy.
While regulation of AI is deemed necessary, it is also suggested that it should not unnecessarily delay or hinder other necessary regulations. The European AI Act, with its risk classes, is mentioned as a good first approach to AI regulation.
The importance of cooperation between the state and industry actors is emphasized. AI is mainly developed by a few big tech players from the US, and there is a need for closer collaboration between the state and industry actors for improved governance and oversight of AI.
It is argued that self-regulation by industries alone is not enough. Establishing a system of transparency on a permanent legal basis is seen as necessary to ensure ethical and responsible AI development and deployment.
Additional resources and stronger supervision of AI are deemed necessary. Authorities responsible for the supervision of AI should be equipped with more financial and personnel resources to effectively monitor and regulate AI activities.
The need for human control in AI-related decision-making is emphasized. Official decisions or decisions made by private companies that can have a negative impact on individuals should not be solely based on AI but should involve human oversight and control.
Safety in AI development is considered paramount. It is emphasized that secure development practices are crucial to ensure the safety and reliability of AI solutions.
Lastly, it is acknowledged that while regulation plays a vital role, it alone cannot completely eliminate all the problems associated with AI. There is a need for a comprehensive approach that combines effective regulation, cooperation, resources, and human control to address the challenges and maximize the benefits of AI technology.
Jochen Michels, Head of Public Affairs Europe, Kaspersky
During the session, all the speakers were in agreement that the six ethical principles of AI use in cybersecurity are equally important. This consensus among the speakers highlights their shared understanding of the significance of each principle in ensuring ethical practices in the field.
Furthermore, the attendees of the session also recognized the importance of all six principles. The fact that these principles were mentioned by multiple participants indicates their collective acknowledgement of the principles' value. This shared significance emphasizes the need to consider all six principles when addressing the ethical challenges posed by AI in cybersecurity.
However, while acknowledging the equal importance of the principles, there is consensus among the participants that further multi-stakeholder discussion is necessary. This discussion should involve a comprehensive range of stakeholders, including industry representatives, academics, and political authorities. By involving all these parties, it becomes possible to ensure a holistic and inclusive approach to addressing the ethical implications of AI use in cybersecurity.
The need for this multi-stakeholder discussion becomes evident through the variety of principles mentioned in a poll conducted during the session. The diverse range of principles brought up by the attendees emphasizes the importance of engaging all involved parties to ensure comprehensive coverage of ethical considerations.
In conclusion, the session affirmed that all six ethical principles of AI use in cybersecurity are of equal importance. However, it also highlighted the necessity for further multi-stakeholder discussion to ensure comprehensive coverage and engagement of all stakeholders. This discussion should involve representatives from industry, academia, and politics to effectively address the ethical challenges posed by AI in cybersecurity. The session underscored the significance of partnerships and cooperation in tackling these challenges on a broader scale.
Moderator
The panel discussion on the ethical principles of AI in cybersecurity brought together experts from various backgrounds. Panelists included Professor Dennis Kenji Kipker, an expert in cybersecurity law from Germany, Professor Amal, the Executive President for the AI Movement at the Moroccan International Center for Artificial Intelligence, Ms. Nushin, a Senior Security Researcher from Kaspersky in Australia, and Ms. Anastasia Kazakova, a Cyber Diplomacy Knowledge Fellow from the Diplo Foundation in Serbia.
The panelists discussed the potential of AI to enhance cybersecurity but stressed the need for a dialogue on ethical principles. AI can automate common tasks and help identify threats in cybersecurity. Kaspersky detects 325,000 new malicious files daily and recognizes the role AI can play in transforming cybersecurity methods. However, AI systems in cybersecurity are vulnerable to attacks and misuse. Adversarial AI can attack AI systems and misuse AI to create fake videos and AI-powered malware.
Transparency, safety, human control, privacy, and defense against cyber attacks were identified as key ethical principles in AI cybersecurity. The panelists emphasized the importance of transparency in understanding the technology being used and protecting user data. They also highlighted the need for human control in decision-making processes, as decisions impacting individuals cannot solely rely on AI algorithms.
The panelists and online audience agreed on the equal importance of these ethical principles and called for further discussions on their implementation. The moderator supported multi-stakeholder discussions and stressed the involvement of various sectors, including industry, research, academia, politics, and civil society, for a comprehensive and inclusive approach.
Plans are underway to develop an impulse paper outlining ethical principles for the use of AI in cybersecurity. This paper will reflect the discussion outcomes and be shared with the IGF community. Feedback from stakeholders will be gathered to further refine the principles. Kaspersky will also use the paper to develop their own ethical principles.
In summary, the panel discussion highlighted the ethical considerations of AI in cybersecurity. Transparency, safety, human control, privacy, and defense against cyber attacks were identified as crucial principles. The ongoing multi-stakeholder discussions and the development of an impulse paper aim to provide guidelines for different sectors and promote an ethical approach to AI in cybersecurity.
Speakers
AE
Amal El Fallah-Seghrouchini
Speech speed
128 words per minute
Speech length
1741 words
Speech time
817 secs
Arguments
AI can enhance and transform cybersecurity
Supporting facts:
- Kaspersky detects like 325,000 new malicious files every day
- AI can automate common cybersecurity tasks
- AI can identify threats in large data sets
Topics: Artificial Intelligence, Cybersecurity
AI in cybersecurity is a national security priority
Supporting facts:
- National security priority by the NSF, NSTC and NASA
Topics: Artificial Intelligence, Cybersecurity
AI systems used in cybersecurity are vulnerable and need regulation
Supporting facts:
- AI systems can be attacked by adversarial machine learning techniques
- AI cannot be made unconditionally safe
Topics: Artificial Intelligence, Cybersecurity, Regulation
AI can create new kinds of cyber attacks
Supporting facts:
- AI can be used for phishing, cyber extortion, automated interactive attacks
Topics: Artificial Intelligence, Cybersecurity
Security is naturally interested in the identity of the person
Topics: Security, Identity
There are initiatives to differentiate between identifier and identity
Topics: Security, Privacy, Identifier, Identity
Reliance on a trusted third party to certify
Topics: Trust, Third-party certification, Security
Avoiding the use of a unique identifier for a person
Supporting facts:
- Avoids direct access to all data of a person
- Sectorial identifiers are associated with the identity through a third-party trust
Topics: Privacy, Identifier
Ethics in AI is not limited to data protection
Supporting facts:
- They are discussing about the application of ethics in AI and its protection.
Topics: ethics, AI, data protection
We should consider dignity and human rights in AI.
Topics: ethics, AI, human rights, dignity
Informed consent in AI systems is critical
Topics: AI, informed consent
People may not be fully aware of the consequences when using generative AI systems.
Topics: AI, user awareness, generative AI systems
Preserving dignity and human rights in all systems is important
Supporting facts:
- Ethics is not just a stamp on products
- Ethics is a continuous debate and discussion
Topics: Ethics, Human Rights, Dignity
Working to reach informed consent with the population that uses these systems is crucial
Supporting facts:
- Didactical explanations are required to explain complex systems
Topics: Ethics, Informed Consent
Report
Artificial Intelligence (AI) has emerged as a powerful tool in the field of cybersecurity, with the potential to enhance and transform existing systems. By leveraging AI, common cybersecurity tasks can be automated, allowing for faster and more efficient detection and response to threats.
AI can also analyze and identify potential threats in large datasets, enabling cybersecurity professionals to stay one step ahead of cybercriminals. The importance of AI in cybersecurity is further highlighted by its recognition as a national security priority. Organizations such as the National Science Foundation (NSF), National Science and Technology Council (NSTC), and National Aeronautics and Space Administration (NASA) have emphasized the significance of AI in maintaining the security of nations.
This recognition demonstrates the growing global awareness of the role that AI can play in safeguarding critical infrastructure and sensitive data. However, the use of AI in cybersecurity also raises concerns about the vulnerability of AI systems. Adversarial machine learning techniques can be deployed to attack AI systems, potentially compromising their effectiveness.
It is crucial to regulate the use of AI in cybersecurity to mitigate these vulnerabilities and ensure the reliability and security of these systems. Furthermore, AI is not only a tool for defending against cyber threats but can also be used to create new kinds of attacks.
For example, AI-powered systems can be utilized for phishing, cyber extortion, and automated interactive attacks. The potential for AI to be used maliciously highlights the need for robust ethical and regulatory considerations in the development and deployment of AI systems in the cybersecurity domain.
Ethical and regulatory considerations are necessary to strike a balance between the power of AI and human control. Complete delegation of control to AI in cybersecurity is not recommended, as human oversight and decision-making are essential. Frameworks should be established to ensure the ethical use of AI and to address concerns related to privacy, data governance, and individual rights.
Initiatives aimed at differentiating between identifier and identity are being pursued to strengthen security and privacy measures. By avoiding the use of a unique identifier for individuals and instead associating sectorial identifiers with identity through trusted third-party certification, the risk of data breaches and unauthorized access is reduced.
In addition to data protection, ethics in AI extend to considerations of dignity and human rights. It is essential to incorporate these ethical principles into the design and implementation of AI systems. Furthermore, informed consent and user awareness are crucial in ensuring that individuals understand the implications and potential risks associated with using generative AI systems.
Preserving dignity and human rights should be a priority in all systems, including those powered by AI. This encompasses a continuous debate and discussion in which the principles of ethics play a central role. Educating the population and working towards informed consent are important steps in achieving a balance between the benefits and potential harms of AI.
Accountability, privacy, and data protection are recognized as tools towards ensuring ethical practices. These principles should be integrated into the development and deployment of AI systems to safeguard individual rights and maintain public trust. Overall, AI has the potential to revolutionize cybersecurity, but its implementation requires careful consideration of ethical, regulatory, and privacy concerns.
While AI can enhance and transform the field of cybersecurity, there is a need for comprehensive regulation to address vulnerabilities. The differentiation between identifier and identity, as well as the emphasis on dignity and human rights, are important factors to consider in deploying AI systems.
Promoting informed consent, user awareness, and ethical use of AI should be prioritized to maintain a secure and trustworthy digital environment.
AK
Anastasiya Kazakova
Speech speed
170 words per minute
Speech length
3082 words
Speech time
1087 secs
Arguments
The usage and operation of AI should not be solely autonomous due to its impactful decisions on everyday life
Supporting facts:
- AI is becoming an integral part of cybersecurity, enhancing threat detection and intelligence gathering
- Users, developers, and policymakers alike still have questions about how AI operates and makes decisions
Topics: AI, Cybersecurity, Policy
Fragmentation and conflicting regulations on AI from different governing bodies may hinder its benefits
Supporting facts:
- There's an anticipation of conflicting AI regulations being passed by large markets such as EU, US, and China
- Fragmentation in AI regulations may limit its benefits and opportunities for different communities
Topics: AI, Policy, International Regulations
AI regulation should focus on outcomes and expectations not the technology itself
Supporting facts:
- There's a difficulty in universally defining AI
- Legislators struggle to carefully scope future laws as it pertains to AI
Topics: AI, Policy
Organizations shouldn't have the right to 'hack back'
Supporting facts:
- Most countries' governments and industries agree organizations shouldn't have this right
- The law enforcement that has the mandate per law should step in and investigate
Topics: Cybersecurity, Law Enforcement, Hacking
The challenges we face in cyberspace are getting more sophisticated
Supporting facts:
- The major difficulty lies in the nuanced nature of the problem, involving both technical and policy solutions
- Enforcement agencies must identify whether the threat is a cyber espionage, an APT, or a complex DDoS
Topics: Cybersecurity, Artificial Intelligence
Regulations are important but not the only solution to address the challenges with AI
Supporting facts:
- Regulations can be slow and not effective to address rapidly developing AI
- The industry can do a lot without policymakers and regulators being in the room
Topics: AI, Regulations, Software Transparency, Industry Initiatives
None of these principles alone do help to achieve a sufficient degree of security
Supporting facts:
- Transparency alone gives knowledge about the technology, the codes used and policies but does not necessarily make us more secure
Topics: cybersecurity, technology, AI
Report
Artificial Intelligence (AI) plays a crucial role in enhancing cybersecurity by improving threat detection and intelligence gathering. However, concerns have been raised regarding the autonomous nature of AI and its potential to make impactful decisions in everyday life. It is argued that AI should not operate solely autonomously, highlighting the importance of human oversight in guiding AI's decision-making processes.
A major issue faced in the field of AI is the anticipation of conflicting AI regulations being established by major markets, including the EU, US, and China. This potential fragmentation in regulations raises concerns about the limitations and hindered benefits of AI.
It is important to have uniform regulations that promote the widespread use and opportunities of AI for different communities. The challenge of defining AI universally is another issue faced by legislators. With AI evolving rapidly, it becomes increasingly difficult to encompass all technological advancements within rigid legal frameworks.
Instead, the focus should be on regulating the outcomes and expectations of AI, rather than the technology itself. This flexible and outcome-driven approach allows for adaptable regulations that keep up with the dynamic nature of AI development. In the realm of cybersecurity, the question arises of whether organizations should have the right to "hack back" in response to attacks.
Most governments and industries agree that organizations should not have this right, as it can lead to escalating cyber conflicts. Instead, it is recommended that law enforcement agencies with the appropriate mandate step in and investigate cyberattacks. The challenges faced in cyberspace are becoming increasingly sophisticated, requiring both technical and policy solutions.
Addressing cyber threats necessitates identifying the nature of the threat, whether it is cyber espionage, an Advanced Persistent Threat (APT), or a complex Distributed Denial of Service (DDoS) attack. Hence, integrated approaches involving both technical expertise and policy frameworks are essential to effectively combat cyber threats.
Ethical behavior is emphasized in the field of cybersecurity. It is crucial for good actors to abide by international and national laws, even in their reactions to unethical actions. Reacting unethically to protect oneself can compromise overall security and stability.
Therefore, ethical guidelines and considerations must guide actions in the cybersecurity realm. The solution to addressing cybersecurity concerns lies in creativity and enhanced cooperation. Developing new types of response strategies and increasing collaboration between communities, vendors, and governments are vital.
While international and national laws provide a foundation, innovative approaches and thinking must be utilized to develop effective responses to emerging cyber threats. Regulations play an important role in addressing AI challenges, but they are not the sole solution. The industry can also make significant strides in enhancing AI ethics, governance, and transparency without solely relying on policymakers and regulators.
Therefore, a balanced approach that combines effective regulations with industry initiatives is necessary. Increased transparency in software and AI-based solution composition is supported. The initiative of a "software bill of materials" is seen as a positive step towards understanding the composition of software, similar to knowing the ingredients of a cake.
Documenting data sources, collection methods, and processing techniques promotes responsible consumption and production. In conclusion, AI has a significant impact on cybersecurity, but it should not operate exclusively autonomously. Addressing challenges such as conflicting regulations, defining AI, the right to "hack back," and increasing sophistication of cyber threats requires a multidimensional approach that encompasses technical expertise, policy frameworks, ethical considerations, creativity, and enhanced cooperation.
Effective regulations, industry initiatives, and transparency in software composition all contribute to a more secure and stable cyberspace.
A
Audience
Speech speed
167 words per minute
Speech length
130 words
Speech time
47 secs
Arguments
Implementing ethical AI in cybersecurity could potentially put us at a disadvantage when countering the threat of unethical adversarial AI
Supporting facts:
- The adversary is going to use adversarial AI and they don't care about ethics
- Engaging in responsive actions by applying ethical AI to counter an unethical adversarial AI might put us in a disadvantage
Topics: Ethical AI, Cybersecurity, Adversarial AI
Report
During the discussion, the speakers delved into the implementation of ethical AI in the field of cybersecurity and raised concerns regarding its potential disadvantages when countering unethical adversarial AI. They emphasised that adversaries employing adversarial AI techniques are unlikely to consider ethical principles and may operate without any regard for the consequences of their actions.
The audience expressed apprehension about the practicality and effectiveness of using ethical AI in defending against unethical adversarial AI. They questioned whether the application of ethical AI would provide a sufficient response to the increasingly sophisticated and malicious tactics employed by adversaries.
It was noted that engaging in responsive actions by deploying ethical AI to counter unethical adversarial AI might place defenders at a disadvantage, highlighting the complexity of the issue. Given these concerns, the need for a thorough review of the application of ethical AI in response to unethical adversarial AI was acknowledged.
There was specific emphasis on active cyber defence, which involves proactive measures to prevent cyber attacks and mitigate potential harm. The aim of the review is to ensure that the use of ethical AI is optimised and effectively aligned with the challenges posed by unethical adversarial AI.
These discussions revolved around the topics of Ethical AI, Adversarial AI, Cybersecurity, and Active Cyber Defence, all of which are highly relevant in today's digital landscape. The concerns raised during the discussion reflect the ongoing tension between the desire to uphold ethical principles and the practical challenges faced when countering adversaries who disregard those principles.
Furthermore, this discussion aligns with the Sustainable Development Goals (SDGs) 9 and 16, which emphasise the importance of creating resilient infrastructure, fostering innovation, promoting peaceful and inclusive societies, and ensuring access to justice for all. By addressing the ethical challenges associated with adversarial AI in cybersecurity, efforts can be made towards achieving these SDGs, as they are integral to building a secure and just digital environment.
Overall, the discussion underscored the need for careful consideration and evaluation of the application of ethical AI in response to unethical adversarial AI. Balancing the ethical dimension with the practical requirements of countering adversaries in the ever-evolving digital landscape is a complex task that warrants ongoing discussion and analysis.
DK
Dennis Kenji Kipker
Speech speed
157 words per minute
Speech length
1961 words
Speech time
747 secs
Arguments
AI and cybersecurity are two topics that have already come together a long time before use cases like generative AI became public.
Supporting facts:
- AI is used with regard to cybersecurity in automated anomaly detection and networks.
- AI is used to improve cybersecurity, to compromise cybersecurity, and AI in general is being developed.
Topics: AI, cybersecurity, generative AI
The regulation of AI and cybersecurity needs clear differentiation between scenarios where AI is one of several possible technical means and the regulation of AI-specific risks themselves.
Topics: AI, regulation, cybersecurity, risks
High impact privacy risks exist when developing AI
Topics: AI development, Data protection, Privacy risks
Struggling in implementation of privacy laws and violation detection
Topics: Privacy laws, law implementation, Violation detection
AI-related decisions should always involve human control
Supporting facts:
- Official decisions, or any kind of decisions made by private companies that could have a negative impact on individuals, cannot be made solely based on AI.
Topics: AI, decision-making, human control, cybersecurity
Safety is paramount in AI development
Supporting facts:
- If AI is not developed securely, safe solutions cannot result.
Topics: AI, safety, security
Report
The discussions revolve around the integration of artificial intelligence (AI) and cybersecurity. AI has already been used in the field of cybersecurity for automated anomaly detection in networks and to improve overall cybersecurity measures. The argument is made that AI and cybersecurity have been interconnected for a long time, even before the emergence of use cases like generative AI.
It is argued that special AI regulation specifically for cybersecurity is not necessary. European lawmakers are mentioned as leaders in cybersecurity legislation, using the term "state-of-the-art of technology" to define the compliance requirements for private companies and public institutions. It is mentioned that attacks using AI can be covered by existing national cyber criminal legislation, without the need for explicit AI-specific regulation.
Furthermore, it is highlighted that the development and security of AI is already addressed in legislation such as the European AI Act. The need for clear differentiation in the regulation of AI and cybersecurity is emphasized. Different scenarios need different approaches, distinguishing between cases where AI is one of several technical means and cases where AI-specific risks need to be regulated.
The privacy risks associated with AI development are also acknowledged. High-impact privacy risks can arise during the development process and need to be carefully considered and addressed. The struggles in implementing privacy laws and detecting violations are mentioned. It is suggested that more efforts are needed to effectively enforce privacy laws and detect violations in order to protect individuals' privacy.
While regulation of AI is deemed necessary, it is also suggested that it should not unnecessarily delay or hinder other necessary regulations. The European AI Act, with its risk classes, is mentioned as a good first approach to AI regulation.
The importance of cooperation between the state and industry actors is emphasized. AI is mainly developed by a few big tech players from the US, and there is a need for closer collaboration between the state and industry actors for improved governance and oversight of AI.
It is argued that self-regulation by industries alone is not enough. Establishing a system of transparency on a permanent legal basis is seen as necessary to ensure ethical and responsible AI development and deployment. Additional resources and stronger supervision of AI are deemed necessary.
Authorities responsible for the supervision of AI should be equipped with more financial and personnel resources to effectively monitor and regulate AI activities. The need for human control in AI-related decision-making is emphasized. Official decisions or decisions made by private companies that can have a negative impact on individuals should not be solely based on AI but should involve human oversight and control.
Safety in AI development is considered paramount. It is emphasized that secure development practices are crucial to ensure the safety and reliability of AI solutions. Lastly, it is acknowledged that while regulation plays a vital role, it alone cannot completely eliminate all the problems associated with AI.
There is a need for a comprehensive approach that combines effective regulation, cooperation, resources, and human control to address the challenges and maximize the benefits of AI technology.
JM
Jochen Michels
Speech speed
123 words per minute
Speech length
82 words
Speech time
40 secs
Arguments
All six ethical principles of AI use in cybersecurity are equally important
Supporting facts:
- All six principles were mentioned by the attendees of the session, indicating their shared significance
Topics: AI ethics, cybersecurity, poll result interpretation
Report
During the session, all the speakers were in agreement that the six ethical principles of AI use in cybersecurity are equally important. This consensus among the speakers highlights their shared understanding of the significance of each principle in ensuring ethical practices in the field.
Furthermore, the attendees of the session also recognized the importance of all six principles. The fact that these principles were mentioned by multiple participants indicates their collective acknowledgement of the principles' value. This shared significance emphasizes the need to consider all six principles when addressing the ethical challenges posed by AI in cybersecurity.
However, while acknowledging the equal importance of the principles, there is consensus among the participants that further multi-stakeholder discussion is necessary. This discussion should involve a comprehensive range of stakeholders, including industry representatives, academics, and political authorities. By involving all these parties, it becomes possible to ensure a holistic and inclusive approach to addressing the ethical implications of AI use in cybersecurity.
The need for this multi-stakeholder discussion becomes evident through the variety of principles mentioned in a poll conducted during the session. The diverse range of principles brought up by the attendees emphasizes the importance of engaging all involved parties to ensure comprehensive coverage of ethical considerations.
In conclusion, the session affirmed that all six ethical principles of AI use in cybersecurity are of equal importance. However, it also highlighted the necessity for further multi-stakeholder discussion to ensure comprehensive coverage and engagement of all stakeholders. This discussion should involve representatives from industry, academia, and politics to effectively address the ethical challenges posed by AI in cybersecurity.
The session underscored the significance of partnerships and cooperation in tackling these challenges on a broader scale.
MB
Martin Boteman
Speech speed
158 words per minute
Speech length
389 words
Speech time
148 secs
Arguments
Security will require identity
Supporting facts:
- A complication is that security will require identity. Data, thanks to AI, become even more often personally identifiable than before
Topics: AI, Cybersecurity, Privacy
Necessity to deal with the dichotomy between identity and privacy
Supporting facts:
- How do you deal with the dichotomy between identity need in the future going forward? There's no way around it. At the same time, also privacy.
Topics: AI, Cybersecurity, Privacy
Legal isn't enough, it is the last resort
Supporting facts:
- AI context is an extra challenge
- Algorithmic Accountability Act in the USA
- European Union's AI Act
Topics: Law, Ethics, Algorithmic Accountability Act, European Union's AI Act
Report
The discussion delves into the significance of identity in the realm of security and the crucial role that AI can play in safeguarding identities. It is acknowledged that with the advancement of AI, data has become more frequently personally identifiable than ever before, leading to a need to address the complex relationship between identity and privacy.
One argument put forward is that security will require identity. The increasing personal identifiability of data, facilitated by AI, has made it imperative to establish and protect individual identities for the sake of security. This argument highlights the evolving nature of security in the digital age and the need to adapt to these changes.
On the other hand, a positive stance is taken towards the potential of AI in enhancing security with the identity factor. It is suggested that AI can aid in securing identities by leveraging its capabilities. The specifics of how AI can contribute to this aspect are not explicitly mentioned, but it is implied that AI can play a role in ensuring the authenticity and integrity of identities.
Furthermore, the discussion recognises the necessity to address the dichotomy between identity and privacy. While identity is essential for security purposes, safeguarding privacy is equally important. This creates a challenge in finding a balance between the two. The analysis raises the question of how to deal with this dichotomy in future endeavours, emphasizing the need for a thoughtful and nuanced approach.
Legal measures are acknowledged as an important consideration in the context of AI. However, it is argued that relying solely on legal frameworks is not enough. This underlines the complexity of regulating AI and the urgent need for additional measures to ensure the responsible and ethical use of the technology.
The mention of the Algorithmic Accountability Act in the USA and the European Union's AI Act serves to highlight the efforts being made to address these concerns. Overall, there is a positive sentiment regarding the potential of AI in enhancing security with the identity factor.
The discussion reinforces the significance of ethical principles such as security by design and privacy by design when implementing AI solutions. It asserts that taking responsibility for AI and incorporating these principles into its development and deployment is essential. It is worth noting that the expanded summary provides a comprehensive overview of the main points discussed.
However, more specific evidence or examples supporting these arguments could have further strengthened the analysis. Nonetheless, the analysis highlights the intersection of identity, privacy, AI, and security and emphasizes the need for responsible and balanced approaches in this rapidly evolving landscape.
M
Moderator
Speech speed
162 words per minute
Speech length
3553 words
Speech time
1313 secs
Arguments
Introduction of all panelists
Supporting facts:
- Panelists include Professor Dennis Kenji Kipker, an expert in cybersecurity law from Germany, Professor Amal, the Executive President for the AI Movement, the Moroccan International Center for Artificial Intelligence, Ms. Nushin, Senior Security Researcher from Kaspersky in Australia, and Ms. Anastasia Kazakova, Cyber Diplomacy Knowledge Fellow from Diplo Foundation in Serbia
Topics: Panel Discussion, AI, Cybersecurity
Setting the context of the workshop
Supporting facts:
- Workshop titled Ethical Principles for the Use of AI in Cybersecurity
- AI has the potential to enhance cybersecurity, but there is a need for a dialogue on ethical principles
- Kaspersky has developed initial ideas regarding aspects that should be taken into account
Topics: AI, Cybersecurity, Ethics
Plan for the session
Supporting facts:
- The session will start with an audience poll, followed by questions to the panelists. The audience will also get a chance to ask questions
Topics: Workshop structure, Interactive Session
AI in cybersecurity can automate common tasks and identify threats
Supporting facts:
- Kaspersky detects 325,000 new malicious files every day
- AI can enhance and transform cybersecurity methods
- AI implementation can occur in all stages of the cybersecurity life cycle (identification, protection, detection, response, restoration)
- AI can secure or attack AI systems and algorithms
Topics: Cybersecurity, Artificial Intelligence
AI has both costs and benefits in cybersecurity
Supporting facts:
- AI can make social engineering attacks more convincing
- Machine learning can help detect spear phishing and other attacks
- Kaspersky uncovers over 400,000 new unique malicious files daily
Topics: AI, cybersecurity, cost-benefit
Education is crucial for users and employees to understand the risks of AI and not fall victim
Supporting facts:
- Attackers can often bypass services, making understanding the environment and its security measures important
- AI can help in making a more convincing conversation or a more convincing spear-phishing email
Topics: education, AI, cybersecurity
Dennis Kenji Kipker believes that the development of AI carries high impact privacy risks
Supporting facts:
- From the European Union perspective speaking, we have a general data protection regulation of personal data also when AI is being trained.
Topics: AI, Privacy
Kipker believes that we should not try to regulate every possible scenario and risk when it comes to AI
Supporting facts:
- A full technology regulation will never be possible and will require a lot of resources to implement.
Topics: AI, Regulation
The detection of violations of AI regulations is more important than the severity of sanctions
Topics: AI, Regulation, Violation detection
Kipker argues that the regulatory debate should not delay or torpedo necessary regulation
Topics: AI, Regulation, Debate
The European AI Act is a good first approach for AI regulation, according to Kipker
Topics: European AI Act, AI, Regulation
Kipker believes it is necessary to establish a system of transparency and improve cooperation between the state and the industry actors
Topics: AI, Cooperation, Transparency
Ethical principles can aid in the supervision of AI but more resources are needed
Topics: AI, Ethics
Legal measures are not enough in ensuring AI security and privacy
Supporting facts:
- Security and Privacy by Design as an enduring principle in the AI context
- Reference to the European Union's AI Act
- Reference to Algorithmic Accountability Act in the USA
Topics: AI security, Legislation, AI and Privacy
The global contextual differences in identity protection
Supporting facts:
- The role of identity can differ, it could protect or even victimize depending on the country
Topics: Identity Protection, International Relations
Transparency and privacy are the most important principles in cybersecurity
Supporting facts:
- Being transparent to users and the rest of the community about what's done with user data
- Importance of protecting users from cyber attacks
- Significance of protecting user data
Topics: Transparency, Privacy, Cybersecurity
Problems cannot be solved by regulation alone
Supporting facts:
- There are many facets and different risks of AI use that regulation might not cover
- Decisions cannot be made solely based on AI
- Politicians might see regulation differently than scientists
Topics: AI, cybersecurity, regulation
Human control over decisions is important
Supporting facts:
- Decisions made by authorities, private companies that might impact individuals cannot be solely based on AI. Humans should be involved in decision making
Topics: AI, cybersecurity, human control
Security is strongly connected with safety in terms of AI
Supporting facts:
- If AI is not developed securely, there can't be safe solutions as its result
Topics: AI, cybersecurity, safety
Ethical principles play a crucial role in ensuring optimal security in cyberspace, although none of the principles alone can achieve the desired level of security.
Supporting facts:
- Transparency alone, while it allows us to understand the technology being used, does not guarantee security.
- Multiple ethical principles, along with other measures, can improve the chances of achieving optimal security.
Topics: Cybersecurity, Artificial Intelligence, Ethical Principles
Plans are underway to develop an impulse paper on ethical principles of AI use in cybersecurity.
Supporting facts:
- The impulse paper will reflect the discussion results and will be made available to the IGF community.
- The paper will be sent to various stakeholders to gather more feedback.
- Kaspersky will use the paper to further develop their own principles.
Topics: Cybersecurity, Artificial Intelligence, Ethical Principles
Efforts are needed to further discussions concerning ethical principles in AI, including transparency, safety, human control, privacy, defense of cybersecurity and openness for dialogue
Supporting facts:
- The panelists and online audience agreed on the equal importance of these principles.
Topics: AI, Ethics, Transparency, Safety, Human Control, Privacy, Cybersecurity, Dialogue, Multi-stakeholder Discussion
Report
The panel discussion on the ethical principles of AI in cybersecurity brought together experts from various backgrounds. Panelists included Professor Dennis Kenji Kipker, an expert in cybersecurity law from Germany, Professor Amal, the Executive President for the AI Movement at the Moroccan International Center for Artificial Intelligence, Ms.
Nushin, a Senior Security Researcher from Kaspersky in Australia, and Ms. Anastasia Kazakova, a Cyber Diplomacy Knowledge Fellow from the Diplo Foundation in Serbia. The panelists discussed the potential of AI to enhance cybersecurity but stressed the need for a dialogue on ethical principles.
AI can automate common tasks and help identify threats in cybersecurity. Kaspersky detects 325,000 new malicious files daily and recognizes the role AI can play in transforming cybersecurity methods. However, AI systems in cybersecurity are vulnerable to attacks and misuse. Adversarial AI can attack AI systems and misuse AI to create fake videos and AI-powered malware.
Transparency, safety, human control, privacy, and defense against cyber attacks were identified as key ethical principles in AI cybersecurity. The panelists emphasized the importance of transparency in understanding the technology being used and protecting user data. They also highlighted the need for human control in decision-making processes, as decisions impacting individuals cannot solely rely on AI algorithms.
The panelists and online audience agreed on the equal importance of these ethical principles and called for further discussions on their implementation. The moderator supported multi-stakeholder discussions and stressed the involvement of various sectors, including industry, research, academia, politics, and civil society, for a comprehensive and inclusive approach.
Plans are underway to develop an impulse paper outlining ethical principles for the use of AI in cybersecurity. This paper will reflect the discussion outcomes and be shared with the IGF community. Feedback from stakeholders will be gathered to further refine the principles.
Kaspersky will also use the paper to develop their own ethical principles. In summary, the panel discussion highlighted the ethical considerations of AI in cybersecurity. Transparency, safety, human control, privacy, and defense against cyber attacks were identified as crucial principles.
The ongoing multi-stakeholder discussions and the development of an impulse paper aim to provide guidelines for different sectors and promote an ethical approach to AI in cybersecurity.
NS
Noushin Shabab
Speech speed
125 words per minute
Speech length
1371 words
Speech time
658 secs
Arguments
AI and machine learning have significantly strengthened cybersecurity
Supporting facts:
- Kaspersky has been using machine learning techniques in their products for a long time
Topics: AI, Machine Learning, Cybersecurity
Transparency is crucial while using AI in cybersecurity
Supporting facts:
- Kaspersky has a global transparency initiative and transparency centers in different countries allowing stakeholders and customers to examine their product code
Topics: AI, Transparency, Cybersecurity
AI and machine learning systems need to be safeguarded from misuse
Supporting facts:
- Attackers can manipulate the outcomes of machine learning systems and algorithms
Topics: AI, Machine Learning, Cybersecurity
Effective use of AI in cybersecurity requires active human involvement
Supporting facts:
- Kaspersky adopts a human control approach in addition to machine learning for analyzing sophisticated malwares
Topics: AI, Machine Learning, Cybersecurity, Human Control
Respect for user privacy is necessary while using AI in cybersecurity
Supporting facts:
- Kaspersky has measures to ensure user privacy in their machine learning algorithms, including pseudonymizing, anonymizing, reducing data collection, and removing personal identifiers
Topics: AI, Privacy, Cybersecurity
AI and machine learning tools should be developed with a primary focus on cybersecurity
Supporting facts:
- Kaspersky only provides services that work in defense and uses AI and machine learning for defensive practices
Topics: AI, Machine Learning, Cybersecurity
Open dialogue and collaboration is key to successful use of AI in cybersecurity
Supporting facts:
- Kaspersky is open for collaboration and believes that only through collaboration can the best results against cyber threats be achieved
Topics: AI, Machine Learning, Cybersecurity, Collaboration
AI can be misused by malicious actors to make more convincing social engineering attacks
Supporting facts:
- AI can enable a more convincing spear phishing email or message that looks harmless
Topics: AI, Cybersecurity, Malware, Social Engineering
Advanced security solutions, particularly those implementing machine learning techniques can help identify such attacks
Topics: Cybersecurity, Machine Learning, Advanced Security Solutions
Raising awareness among users is crucial to protect them from falling victim to such attacks
Supporting facts:
- Education for common users and employees in organizations can help them understand the risks
Topics: Cybersecurity Awareness, User Education
Transparency is crucial in cybersecurity
Supporting facts:
- Being transparent to the users and also to the rest of the community and world, what we do with the user data and how we implement detections and how we protect users
Topics: cybersecurity, transparency
Privacy is fundamental in cybersecurity
Supporting facts:
- We are in cyber security industry and we deal with targets and victims of cyber attacks. For us, it's one of the most important aspects to protect users
Topics: cybersecurity, privacy
Report
Kaspersky, a leading cybersecurity company, has harnessed the power of artificial intelligence (AI) and machine learning to strengthen cybersecurity. They have integrated machine learning techniques into their products for an extended period, resulting in significant improvements. Transparency is paramount when using AI in cybersecurity, according to Kaspersky.
To achieve this, they have implemented a global transparency initiative and established transparency centers in various countries. These centers allow stakeholders and customers to access and review their product code, fostering trust and collaboration in the cybersecurity field. While AI and machine learning have proven effective in cybersecurity, it is crucial to protect these systems from misuse.
Attackers can manipulate machine learning outcomes, posing a significant threat. Safeguards and security measures must be implemented to ensure the integrity of AI and machine learning systems. Kaspersky believes that effective cybersecurity requires a balance between AI and human control.
While machine learning algorithms are adept at analyzing complex malware, human involvement is essential for informed decision-making and responding to evolving threats. Kaspersky combines human control with machine learning to ensure comprehensive cybersecurity practices. Respecting user privacy is another vital consideration when incorporating AI in cybersecurity.
Kaspersky has implemented measures such as pseudonymization, anonymization, data minimization, and personal identifier removal to protect user privacy. By prioritizing user privacy, Kaspersky provides secure and trustworthy solutions. Collaboration and open dialogue are emphasized by Kaspersky in the AI-enabled cybersecurity domain.
They advocate for collective efforts and knowledge exchange to combat cyber threats effectively. Open dialogue promotes the sharing of insights and ideas, leading to stronger cybersecurity practices. It is crucial to be aware of the potential misuse of AI by malicious actors.
AI can facilitate more convincing social engineering attacks, like spear-phishing, which can deceive even vigilant users. However, Kaspersky highlights that advanced security solutions, incorporating machine learning, can identify and mitigate such attacks. User awareness and education are essential to counter AI-enabled cyber threats.
Kaspersky underscores the importance of educating users to understand and effectively respond to these threats. Combining advanced security solutions with user education is a recommended approach to tackle AI-enabled cyber threats. In conclusion, Kaspersky's approach to AI-enabled cybersecurity encompasses leveraging machine learning, maintaining transparency, safeguarding systems, respecting user privacy, and promoting collaboration and user education.
By adhering to these principles, Kaspersky aims to enhance cybersecurity practices and protect users from evolving threats.