“AI is the new electricity” proclaims Andrew Ng, co-founder of Google Brain. Just as we need to know how to safely harness electricity, we also need to know how to securely employ AI to power our businesses. In some scenarios, the security of AI systems can impact human safety. On the flip side, AI can also be misused by cyber-adversaries and so we need to understand how to counter them.
This talk will provide food for thought in 3 areas:
Security of AI systems
Use of AI in cybersecurity
Malicious use of AI
Security in the age of Artificial IntelligenceFaction XYZ
Keynote Presentation for ISACA Belgium 2017 on how artificial intelligence is influencing the cyber security industry, and what current and future developments there are
I was invited to present a talk on "Artificial Intelligence for Cyber Security" for #GirlsInAIHack2021 by #TeenInAIFiji. It was my honor to be there and share my words with the participants and I wish all the participants the best wishes.
Girls from 25 counties aged 12-18 had participated in this Hackathon. They were using Hot Technologies like AI and ML to fight world problems to make good. The event was started on #InternationalWomensDay2021. Total of 1000 participations
500+ Mentors & Organizers
120+ International Speakers were part of it
You can watch it here - https://youtu.be/rhWyt68yuI0
If you want to invite me for a webinar or conference connect
mail: hello@priyanshuratnakar.com or priyanshuratnakar@protonmail.com
You can use the slides but give credit somewhere
For Reference watch my YouTube Video - https://youtu.be/NqvNFwa0hQc
Hey Everyone!
This is my complete talk in a virtual conference for cybersecurity researchers that has been hosted by Bsides Maharashtra and thanks to them that they provided me an opportunity to share my thoughts and knowledge with passionate and budding cybersecurity researchers, Hackers, Bug Hunters, and geeks. My talk is all about the detailed explanation of AI in Cyber Security and this should be listened to by every Cyber Sec Person who wants to learn about How AI Can Help In Cyber Security. I have explained the most and every basic to advance information. So do give it a look and understand the concepts and share as much as you can. Thank you Bsides Maharashtra for inviting me. I am happy and excited to be a part of your event.
If you want to invite me for a webinar or conference connect
mail: hello@priyanshuratnakar.com or priyanshuratnakar@protonmail.com
vent details
Date - 25th to 27th November 2020
CTF
Workshop
Speaker session
website - https://bsidesmaharashtra.com/
Security BSides is a community-driven framework for building events by and for information security community members. These events are already happening in major cities all over the world! We are responsible for organizing an independent BSides approved event for Delhi, India. We’re a volunteer organized event (we have no paid staff), and we truly strive to keep information accessible for everyone.
The idea behind the Security BSides Delhi is to organize an Information Security gathering where professionals, experts, researchers, and InfoSec enthusiasts come together to discuss. It creates opportunities for individuals to both presents and participates in an intimate atmosphere that encourages collaboration. It is an intense event with discussions, demos, and interaction from participants. It is where conversations for the next-big-thing are happening.
Feel free to use the slide but give credit somewhere :)
How is ai important to the future of cyber security Robert Smith
Today’s era is driven by technology in every aspect of our lives, so much that we’ve now increased our dependence on technology on a daily basis. With an increase in the dependency, we’re now very vulnerable and exposed to the intermittent threat posed as cyber-attacks. Cyber-attack threats have plagued businesses, corporates, governments, and institutions.
Every single security company is talking about how they are using machine learning—as a security company you have to claim artificial intelligence to be even part of the conversation. However, this approach can be dangerous when we blindly rely on algorithms to do the right thing. Rather than building systems with actual security knowledge, companies are using algorithms that nobody understands and, in turn, discovering wrong insights.
In this session, we will discuss:
• Limitations of machine learning and issues of explainability
• Where deep learning should never be applied
• Examples of how the blind application of algorithms can lead to wrong results
Security in the age of Artificial IntelligenceFaction XYZ
Keynote Presentation for ISACA Belgium 2017 on how artificial intelligence is influencing the cyber security industry, and what current and future developments there are
I was invited to present a talk on "Artificial Intelligence for Cyber Security" for #GirlsInAIHack2021 by #TeenInAIFiji. It was my honor to be there and share my words with the participants and I wish all the participants the best wishes.
Girls from 25 counties aged 12-18 had participated in this Hackathon. They were using Hot Technologies like AI and ML to fight world problems to make good. The event was started on #InternationalWomensDay2021. Total of 1000 participations
500+ Mentors & Organizers
120+ International Speakers were part of it
You can watch it here - https://youtu.be/rhWyt68yuI0
If you want to invite me for a webinar or conference connect
mail: hello@priyanshuratnakar.com or priyanshuratnakar@protonmail.com
You can use the slides but give credit somewhere
For Reference watch my YouTube Video - https://youtu.be/NqvNFwa0hQc
Hey Everyone!
This is my complete talk in a virtual conference for cybersecurity researchers that has been hosted by Bsides Maharashtra and thanks to them that they provided me an opportunity to share my thoughts and knowledge with passionate and budding cybersecurity researchers, Hackers, Bug Hunters, and geeks. My talk is all about the detailed explanation of AI in Cyber Security and this should be listened to by every Cyber Sec Person who wants to learn about How AI Can Help In Cyber Security. I have explained the most and every basic to advance information. So do give it a look and understand the concepts and share as much as you can. Thank you Bsides Maharashtra for inviting me. I am happy and excited to be a part of your event.
If you want to invite me for a webinar or conference connect
mail: hello@priyanshuratnakar.com or priyanshuratnakar@protonmail.com
vent details
Date - 25th to 27th November 2020
CTF
Workshop
Speaker session
website - https://bsidesmaharashtra.com/
Security BSides is a community-driven framework for building events by and for information security community members. These events are already happening in major cities all over the world! We are responsible for organizing an independent BSides approved event for Delhi, India. We’re a volunteer organized event (we have no paid staff), and we truly strive to keep information accessible for everyone.
The idea behind the Security BSides Delhi is to organize an Information Security gathering where professionals, experts, researchers, and InfoSec enthusiasts come together to discuss. It creates opportunities for individuals to both presents and participates in an intimate atmosphere that encourages collaboration. It is an intense event with discussions, demos, and interaction from participants. It is where conversations for the next-big-thing are happening.
Feel free to use the slide but give credit somewhere :)
How is ai important to the future of cyber security Robert Smith
Today’s era is driven by technology in every aspect of our lives, so much that we’ve now increased our dependence on technology on a daily basis. With an increase in the dependency, we’re now very vulnerable and exposed to the intermittent threat posed as cyber-attacks. Cyber-attack threats have plagued businesses, corporates, governments, and institutions.
Every single security company is talking about how they are using machine learning—as a security company you have to claim artificial intelligence to be even part of the conversation. However, this approach can be dangerous when we blindly rely on algorithms to do the right thing. Rather than building systems with actual security knowledge, companies are using algorithms that nobody understands and, in turn, discovering wrong insights.
In this session, we will discuss:
• Limitations of machine learning and issues of explainability
• Where deep learning should never be applied
• Examples of how the blind application of algorithms can lead to wrong results
Responsible AI & Cybersecurity: A tale of two technology risksLiming Zhu
With the broader adoption of digital technologies and AI, organisations face the emerging risks of AI, the unfamiliar, and the intensified risk of cybersecurity, the familiar. AI and cybersecurity are intertwined, but risk silos are often created when they are dealt with at the technology and governance levels. This talk will explore the interactions between responsible AI and cybersecurity risks via industry case studies. It will show how we can break down the risk silos and use emerging trust-enhancing technologies, architecture and end-to-end software engineering/DevOps practices to connect the two worlds and uplift the risk management posture for both.
AI In Cybersecurity – Challenges and SolutionsZoneFox
With the rise of automation and artificial intelligence, you may be wondering how much of an impact this has on IT security. The question is, where will the future of machine learning and AI in cybersecurity take us and what are the limitations and advantages this technology offers in defending against the insider threat?
Join us to find out more about AI and where you should be applying it right now.
Learning outcomes:
The current state of AI practice and research, and how this is impacting its use in cyber security
What the current strengths and weaknesses are with existing AI approaches
What next generation AI will deliver for us with regards to ensuring we can promptly detect and respond to security incidents
How Machine Learning & AI Will Improve Cyber SecurityDevOps.com
Machine Learning (ML) and Artificial Intelligence (AI) have been proclaimed as perhaps the next great leap in human quality of life, as well as a potential reason for our extinction. Somewhere in between lies how ML & AI can potentially improve our Cyber Security efforts. But are ML & AI a true panacea or merely the next shiny trinket for the cyber industry to fixate on? In this webinar we will explore:
How ML & AI are currently being utilized in cyber security efforts.
What is working and what has not worked
What is on the both the short term and near-term horizon for ML &AI
Practical steps you can take now to begin leveraging these technologies to tangibly improve your cyber security posture
Join our panel of industry experts as we explore this brave new frontier in cyber security with a candid look cutting through the hype.
Artificial Intelligence and Machine Learning for CybersecurityDr David Probert
The talk discusses the application of artificial intelligence and machine learning to enterprise cybersecurity. The topics include self-learning, stochastic cellular automata, adaptive & self-organising systems and recursive Bayesian algorithms. The talk briefly surveys several cybersecurity companies including Darktrace, Logrhythm and Norse Corporation. There is also discussion of the application of AI and neural networks within the Banking sector for "Algorithmic Trading" during the last 10 to 20 years. These techniques are now highly relevant, and even ESSENTIAL, for the provision of real-time enterprise cybersecurity to complement traditional "signature" based anti-virus & firewall based solutions. The talk closes with the presentations for the future of Cybersecurity in 2020, 2025 and 2040 including reference to similar forecasts from both Business & Governments. The talk was given by Dr David Eric Probert at the East-West International Security Conference at the Melia Galgos Hotel in Madrid, Spain on the Tuesday 27th October 2015.
Impact of Generative AI in Cybersecurity - How can ISO/IEC 27032 help?PECB
Generative AI offers great opportunities for innovation in various industries. Hence, by adopting ISO/IEC 27032, you can enhance your cybersecurity resilience and efficiently address the risks associated with generative AI.
Amongst others, the webinar covers:
• AI & Privacy
• Generative AI, Models & Cybersecurity
• AI & ISO/IEC 27032
Presenters:
Christian Grafenauer
Anonymization expert, privacy engineer, data protection officer, LegalTech researcher (GDPR, Blockchain, AI) Christian Grafenauer is an accomplished privacy engineer, anonymization expert, and computer science specialist, currently serving as the project lead for anonymity assessments at techgdpr. With an extensive background as a senior architect in Blockchain for IBM and years of research in the field since 2013, Christian co-founded privacy by Blockchain design to explore the potential of Blockchain technology in revolutionizing privacy and internet infrastructure. As a dedicated advocate for integrating legal and computer science disciplines, Christian’s expertise in anonymization and GDPR compliance enables innovative AI applications, ensuring a seamless fusion of technology and governance, particularly in the realm of smart contracts. In his role at techgdpr, he supports technical compliance, Blockchain, and AI initiatives, along with anonymity assessments. Christian also represents consumer interests as a member of the national Blockchain and DTL standardization committee at din (German standardization institute) in ISO/TC 307.
Akin Johnson
Akin J. Johnson is a renowned Cybersecurity Expert, known for his expertise in protecting digital systems from potential threats. With over a decade of experience in the field, Akin has developed a deep understanding of the ever-evolving cyber landscape.
Akin is an advocate for cybersecurity awareness and frequently shares his knowledge through speaking engagements, workshops, and publications. He firmly believes in the importance of educating individuals and organizations on the best practices for safeguarding their digital assets.
Lucas Falivene
Lucas is a highly experienced cybersecurity professional with a solid base in business, information systems, information security, and cybersecurity policy-making. A former Fulbright scholar with a Master of Science degree in Information Security Policy and Management at Carnegie Mellon University (Highest distinction) and a Master's degree in Information Security at the University of Buenos Aires (Class rank 1st). Lucas has participated in several trainings conducted by the FBI, INTERPOL, OAS, and SEI/CERT as well as in the development of 4 cyber ISO national standards.
Date: July 26, 2023
YouTube Link: https://youtu.be/QPDcROniUcc
Combating Cyber Security Using Artificial IntelligenceInderjeet Singh
Cyber Security & Data Protection India Summit 2018 aims to convene the best minds in Cybersecurity under one roof to create an interactive milieu for exchange of knowledge and ideas. The event will endeavour to address the emerging and continuing threats to Cybersecurity and its changing landscape, as well as respond to increasing risk of security breaches and security governance, application security, cloud based security, Network, Mobile and endpoint security and other cyber risks in the India and abroad.
Privacy in AI/ML Systems: Practical Challenges and Lessons LearnedKrishnaram Kenthapadi
How do we protect the privacy of users when building large-scale AI based systems? How do we develop machine learning models and systems taking fairness, accuracy, explainability, and transparency into account? Model fairness and explainability and protection of user privacy are considered prerequisites for building trust and adoption of AI systems in high stakes domains. We will first motivate the need for adopting a “fairness, explainability, and privacy by design” approach when developing AI/ML models and systems for different consumer and enterprise applications from the societal, regulatory, customer, end-user, and model developer perspectives. We will then focus on the application of privacy-preserving AI techniques in practice through industry case studies. We will discuss the sociotechnical dimensions and practical challenges, and conclude with the key takeaways and open challenges.
Use of Artificial Intelligence in Cyber Security - Avantika UniversityAvantika University
There are many uses of artificial intelligence in cyber security. Although artificial intelligence has so many advantages over human intelligence, it is dependent on humans. Due to the ever-increasing demand for engineers, there is a bright scope in the field of cyber security. Avantika University is one of the top engineering colleges in India.
To know more details, visit us at : https://www.avantikauniversity.edu.in/engineering-colleges/use-of-artificial-intelligence-in-cyber-security.php
This deck is from Interpol Conference 2017, these slides shows the holistic view of machine learning in cyber security for better organization readiness
Cyber Security.
Watch my videos on snack here: --> --> http://sck.io/x-B1f0Iy
@ Kindly Follow my Instagram Page to discuss about your mental health problems-
-----> https://instagram.com/mentality_streak?utm_medium=copy_link
@ Appreciate my work:
-----> behance.net/burhanahmed1
Thank-you !
How do we protect privacy of users when building large-scale AI based systems? How do we develop machine learned models and systems taking fairness, accountability, and transparency into account? With the ongoing explosive growth of AI/ML models and systems, these are some of the ethical, legal, and technical challenges encountered by researchers and practitioners alike. In this talk, we will first motivate the need for adopting a "fairness and privacy by design" approach when developing AI/ML models and systems for different consumer and enterprise applications. We will then focus on the application of fairness-aware machine learning and privacy-preserving data mining techniques in practice, by presenting case studies spanning different LinkedIn applications (such as fairness-aware talent search ranking, privacy-preserving analytics, and LinkedIn Salary privacy & security design), and conclude with the key takeaways and open challenges.
AI & ML in Cyber Security - Why Algorithms are DangerousRaffael Marty
Link to the video of the presentation: https://www.youtube.com/watch?v=WG1k-Xh1TqM
Every single security company is talking in some way or another about how they are applying machine learning. Companies go out of their way to make sure they mention machine learning and not statistics when they explain how they work. Recently, that's not enough anymore either. As a security company you have to claim artificial intelligence to be even part of the conversation.
Guess what. It's all baloney. We have entered a state in cyber security that is, in fact, dangerous. We are blindly relying on algorithms to do the right thing. We are letting deep learning algorithms detect anomalies in our data without having a clue what that algorithm just did. In academia, they call this the lack of explainability and verifiability. But rather than building systems with actual security knowledge, companies are using algorithms that nobody understands and in turn discover wrong insights.
In this talk, I will show the limitations of machine learning, outline the issues of explainability, and show where deep learning should never be applied. I will show examples of how the blind application of algorithms (including deep learning) actually leads to wrong results. Algorithms are dangerous. We need to revert back to experts and invest in systems that learn from, and absorb the knowledge, of experts.
Overview of Artificial Intelligence in CybersecurityOlivier Busolini
If you are interested in understsanding a bit more the potential of Artifical Intelligence in Cybersecurity, you might want to have a look at this overview.
Written from my CISO -and non AI expert- point of view, for fellow security professional to navigate the AI hype, and (hopefully!) make better, informed decisions :-)
All feedback welcome !
Today, I will be presenting on the topic of
"Generative AI, responsible innovation, and the law."
Artificial Intelligence has been making rapid strides in recent years,
and its applications are becoming increasingly diverse.
Generative AI, in particular, has emerged as a promising area of innovation, the potential to create highly realistic and compelling outputs.
“AI techniques in cyber-security applications”. Flammini lnu susec19Francesco Flammini
▪ “AI techniques in cyber-security applications”. Invited speech at “Sunetdagarna våren 2019” (conference of the association of Swedish universities), April 1-4 2019, Växjö, Sweden.
AI and Machine Learning In Cybersecurity | A Saviour or Enemy?SahilRao25
Let's take a look at implementations of AI or machine learning in the cybersecurity world. To know more: https://www.softwarefirms.co/blog/ai-and-machine-learning-in-cybersecurity-a-saviour-or-enemy?utm_source=Social+media&utm_medium=Traffic&utm_campaign=SR
A technical seminar delivered on Machine learning in cybersecurity. Machine learning is trending and desired subject this presentation demonstrates how machine learning can be used to protect IT infrastructure
Generative AI's impact on creativity and productivity is undeniable. This presentation dives into real-world security and privacy risks, along with methods to address them. Can generative AI be used for cybersecurity? Let's explore!
AI Cybersecurity: Pros & Cons. AI is reshaping cybersecurityTasnim Alasali
Discover how AI is reshaping cybersecurity. This presentation delves into AI's role in enhancing threat detection, the balance of innovation and risk, and the strategies shaping the future of digital defense.
Responsible AI & Cybersecurity: A tale of two technology risksLiming Zhu
With the broader adoption of digital technologies and AI, organisations face the emerging risks of AI, the unfamiliar, and the intensified risk of cybersecurity, the familiar. AI and cybersecurity are intertwined, but risk silos are often created when they are dealt with at the technology and governance levels. This talk will explore the interactions between responsible AI and cybersecurity risks via industry case studies. It will show how we can break down the risk silos and use emerging trust-enhancing technologies, architecture and end-to-end software engineering/DevOps practices to connect the two worlds and uplift the risk management posture for both.
AI In Cybersecurity – Challenges and SolutionsZoneFox
With the rise of automation and artificial intelligence, you may be wondering how much of an impact this has on IT security. The question is, where will the future of machine learning and AI in cybersecurity take us and what are the limitations and advantages this technology offers in defending against the insider threat?
Join us to find out more about AI and where you should be applying it right now.
Learning outcomes:
The current state of AI practice and research, and how this is impacting its use in cyber security
What the current strengths and weaknesses are with existing AI approaches
What next generation AI will deliver for us with regards to ensuring we can promptly detect and respond to security incidents
How Machine Learning & AI Will Improve Cyber SecurityDevOps.com
Machine Learning (ML) and Artificial Intelligence (AI) have been proclaimed as perhaps the next great leap in human quality of life, as well as a potential reason for our extinction. Somewhere in between lies how ML & AI can potentially improve our Cyber Security efforts. But are ML & AI a true panacea or merely the next shiny trinket for the cyber industry to fixate on? In this webinar we will explore:
How ML & AI are currently being utilized in cyber security efforts.
What is working and what has not worked
What is on the both the short term and near-term horizon for ML &AI
Practical steps you can take now to begin leveraging these technologies to tangibly improve your cyber security posture
Join our panel of industry experts as we explore this brave new frontier in cyber security with a candid look cutting through the hype.
Artificial Intelligence and Machine Learning for CybersecurityDr David Probert
The talk discusses the application of artificial intelligence and machine learning to enterprise cybersecurity. The topics include self-learning, stochastic cellular automata, adaptive & self-organising systems and recursive Bayesian algorithms. The talk briefly surveys several cybersecurity companies including Darktrace, Logrhythm and Norse Corporation. There is also discussion of the application of AI and neural networks within the Banking sector for "Algorithmic Trading" during the last 10 to 20 years. These techniques are now highly relevant, and even ESSENTIAL, for the provision of real-time enterprise cybersecurity to complement traditional "signature" based anti-virus & firewall based solutions. The talk closes with the presentations for the future of Cybersecurity in 2020, 2025 and 2040 including reference to similar forecasts from both Business & Governments. The talk was given by Dr David Eric Probert at the East-West International Security Conference at the Melia Galgos Hotel in Madrid, Spain on the Tuesday 27th October 2015.
Impact of Generative AI in Cybersecurity - How can ISO/IEC 27032 help?PECB
Generative AI offers great opportunities for innovation in various industries. Hence, by adopting ISO/IEC 27032, you can enhance your cybersecurity resilience and efficiently address the risks associated with generative AI.
Amongst others, the webinar covers:
• AI & Privacy
• Generative AI, Models & Cybersecurity
• AI & ISO/IEC 27032
Presenters:
Christian Grafenauer
Anonymization expert, privacy engineer, data protection officer, LegalTech researcher (GDPR, Blockchain, AI) Christian Grafenauer is an accomplished privacy engineer, anonymization expert, and computer science specialist, currently serving as the project lead for anonymity assessments at techgdpr. With an extensive background as a senior architect in Blockchain for IBM and years of research in the field since 2013, Christian co-founded privacy by Blockchain design to explore the potential of Blockchain technology in revolutionizing privacy and internet infrastructure. As a dedicated advocate for integrating legal and computer science disciplines, Christian’s expertise in anonymization and GDPR compliance enables innovative AI applications, ensuring a seamless fusion of technology and governance, particularly in the realm of smart contracts. In his role at techgdpr, he supports technical compliance, Blockchain, and AI initiatives, along with anonymity assessments. Christian also represents consumer interests as a member of the national Blockchain and DTL standardization committee at din (German standardization institute) in ISO/TC 307.
Akin Johnson
Akin J. Johnson is a renowned Cybersecurity Expert, known for his expertise in protecting digital systems from potential threats. With over a decade of experience in the field, Akin has developed a deep understanding of the ever-evolving cyber landscape.
Akin is an advocate for cybersecurity awareness and frequently shares his knowledge through speaking engagements, workshops, and publications. He firmly believes in the importance of educating individuals and organizations on the best practices for safeguarding their digital assets.
Lucas Falivene
Lucas is a highly experienced cybersecurity professional with a solid base in business, information systems, information security, and cybersecurity policy-making. A former Fulbright scholar with a Master of Science degree in Information Security Policy and Management at Carnegie Mellon University (Highest distinction) and a Master's degree in Information Security at the University of Buenos Aires (Class rank 1st). Lucas has participated in several trainings conducted by the FBI, INTERPOL, OAS, and SEI/CERT as well as in the development of 4 cyber ISO national standards.
Date: July 26, 2023
YouTube Link: https://youtu.be/QPDcROniUcc
Combating Cyber Security Using Artificial IntelligenceInderjeet Singh
Cyber Security & Data Protection India Summit 2018 aims to convene the best minds in Cybersecurity under one roof to create an interactive milieu for exchange of knowledge and ideas. The event will endeavour to address the emerging and continuing threats to Cybersecurity and its changing landscape, as well as respond to increasing risk of security breaches and security governance, application security, cloud based security, Network, Mobile and endpoint security and other cyber risks in the India and abroad.
Privacy in AI/ML Systems: Practical Challenges and Lessons LearnedKrishnaram Kenthapadi
How do we protect the privacy of users when building large-scale AI based systems? How do we develop machine learning models and systems taking fairness, accuracy, explainability, and transparency into account? Model fairness and explainability and protection of user privacy are considered prerequisites for building trust and adoption of AI systems in high stakes domains. We will first motivate the need for adopting a “fairness, explainability, and privacy by design” approach when developing AI/ML models and systems for different consumer and enterprise applications from the societal, regulatory, customer, end-user, and model developer perspectives. We will then focus on the application of privacy-preserving AI techniques in practice through industry case studies. We will discuss the sociotechnical dimensions and practical challenges, and conclude with the key takeaways and open challenges.
Use of Artificial Intelligence in Cyber Security - Avantika UniversityAvantika University
There are many uses of artificial intelligence in cyber security. Although artificial intelligence has so many advantages over human intelligence, it is dependent on humans. Due to the ever-increasing demand for engineers, there is a bright scope in the field of cyber security. Avantika University is one of the top engineering colleges in India.
To know more details, visit us at : https://www.avantikauniversity.edu.in/engineering-colleges/use-of-artificial-intelligence-in-cyber-security.php
This deck is from Interpol Conference 2017, these slides shows the holistic view of machine learning in cyber security for better organization readiness
Cyber Security.
Watch my videos on snack here: --> --> http://sck.io/x-B1f0Iy
@ Kindly Follow my Instagram Page to discuss about your mental health problems-
-----> https://instagram.com/mentality_streak?utm_medium=copy_link
@ Appreciate my work:
-----> behance.net/burhanahmed1
Thank-you !
How do we protect privacy of users when building large-scale AI based systems? How do we develop machine learned models and systems taking fairness, accountability, and transparency into account? With the ongoing explosive growth of AI/ML models and systems, these are some of the ethical, legal, and technical challenges encountered by researchers and practitioners alike. In this talk, we will first motivate the need for adopting a "fairness and privacy by design" approach when developing AI/ML models and systems for different consumer and enterprise applications. We will then focus on the application of fairness-aware machine learning and privacy-preserving data mining techniques in practice, by presenting case studies spanning different LinkedIn applications (such as fairness-aware talent search ranking, privacy-preserving analytics, and LinkedIn Salary privacy & security design), and conclude with the key takeaways and open challenges.
AI & ML in Cyber Security - Why Algorithms are DangerousRaffael Marty
Link to the video of the presentation: https://www.youtube.com/watch?v=WG1k-Xh1TqM
Every single security company is talking in some way or another about how they are applying machine learning. Companies go out of their way to make sure they mention machine learning and not statistics when they explain how they work. Recently, that's not enough anymore either. As a security company you have to claim artificial intelligence to be even part of the conversation.
Guess what. It's all baloney. We have entered a state in cyber security that is, in fact, dangerous. We are blindly relying on algorithms to do the right thing. We are letting deep learning algorithms detect anomalies in our data without having a clue what that algorithm just did. In academia, they call this the lack of explainability and verifiability. But rather than building systems with actual security knowledge, companies are using algorithms that nobody understands and in turn discover wrong insights.
In this talk, I will show the limitations of machine learning, outline the issues of explainability, and show where deep learning should never be applied. I will show examples of how the blind application of algorithms (including deep learning) actually leads to wrong results. Algorithms are dangerous. We need to revert back to experts and invest in systems that learn from, and absorb the knowledge, of experts.
Overview of Artificial Intelligence in CybersecurityOlivier Busolini
If you are interested in understsanding a bit more the potential of Artifical Intelligence in Cybersecurity, you might want to have a look at this overview.
Written from my CISO -and non AI expert- point of view, for fellow security professional to navigate the AI hype, and (hopefully!) make better, informed decisions :-)
All feedback welcome !
Today, I will be presenting on the topic of
"Generative AI, responsible innovation, and the law."
Artificial Intelligence has been making rapid strides in recent years,
and its applications are becoming increasingly diverse.
Generative AI, in particular, has emerged as a promising area of innovation, the potential to create highly realistic and compelling outputs.
“AI techniques in cyber-security applications”. Flammini lnu susec19Francesco Flammini
▪ “AI techniques in cyber-security applications”. Invited speech at “Sunetdagarna våren 2019” (conference of the association of Swedish universities), April 1-4 2019, Växjö, Sweden.
AI and Machine Learning In Cybersecurity | A Saviour or Enemy?SahilRao25
Let's take a look at implementations of AI or machine learning in the cybersecurity world. To know more: https://www.softwarefirms.co/blog/ai-and-machine-learning-in-cybersecurity-a-saviour-or-enemy?utm_source=Social+media&utm_medium=Traffic&utm_campaign=SR
A technical seminar delivered on Machine learning in cybersecurity. Machine learning is trending and desired subject this presentation demonstrates how machine learning can be used to protect IT infrastructure
Generative AI's impact on creativity and productivity is undeniable. This presentation dives into real-world security and privacy risks, along with methods to address them. Can generative AI be used for cybersecurity? Let's explore!
AI Cybersecurity: Pros & Cons. AI is reshaping cybersecurityTasnim Alasali
Discover how AI is reshaping cybersecurity. This presentation delves into AI's role in enhancing threat detection, the balance of innovation and risk, and the strategies shaping the future of digital defense.
Ai and Design: When, Why and How? - Morgenbooster1508 A/S
This year, A and I became the probably most used letters in the alphabet. Time to reflect upon the role we play as designers in an increasingly AI-driven landscape.
[DSC Europe 23] Shahab Anbarjafari - Generative AI: Impact of Responsible AIDataScienceConferenc1
Today, we embark on a journey into the realm of Generative AI (Gen AI), a force of innovation and possibility. We'll not only unveil the vast opportunities it offers but also confront the ethical challenges it poses. In the spirit of responsible innovation, we'll then dive deep into Responsible AI, illuminating the path to its implementation in this era of Gen AI. Join us for a profound exploration of this technological frontier, where our commitment to responsibility and foresight shapes the future.
Testing Application Security: The Hacker Psyche ExposedTechWell
Computer hacking isn’t a new thing, but the threat is real and growing even today. It is always the attacker’s advantage and the defender’s dilemma. How do you keep your secrets safe and your data protected? In today’s ever-changing technology landscape, the fundamentals of producing secure code and systems are more important than ever. Exploring the psyche of hackers, Mike Benkovich exposes how they think, reveals common areas where they find weakness, and identifies novel ways to test your defenses against their threats. From injection attacks and cross-site scripting to security mis-configuring and broken session management, Mike examines the top exploits, shows you how they work, explores ways to test for them, and then shares what you can do to help your team build more secure software in the future. Join Mike and help your company avoid being at the center of the next media frenzy over lost or compromised data.
First line of defense for cybersecurity : AIAhmed Banafa
The year 2017 wasn't a great year for cyber-security; we saw a large number of high-profile cyber attacks; including Uber, Deloitte, Equifax and the now infamous WannaCry ransomware attack, and 2018 started with a bang too with the hacking of Winter Olympics.
The frightening truth about increasingly cyber-attacks is that most businesses and the cybersecurity industry itself are not prepared. Despite the constant flow of security updates and patches, the number of attacks continues to rise.
AI can help identify threats, direct incident response, and distinguish malware attacks before they cause harm.Learn how AI can help with cybersecurity.
#ATAGTR2019 Presentation "Security testing using ML(Machine learning), AI(Art...Agile Testing Alliance
Pankaj Kumar who is a Principal Quality Engineer at Allscripts took a Session on "Security testing using ML(Machine learning), AI(Artifical intelligence), Deep learning(DL)" at Global Testing Retreat #ATAGTR2019
Please refer our following post for session details:
https://atablogs.agiletestingalliance.org/2019/12/05/global-testing-retreat-atagtr2019-welcomes-pankaj-kumar-as-our-esteemed-speaker/
Digital Forensics for Artificial Intelligence (AI ) Systems.pdfMahdi_Fahmideh
Digital Forensics for Artificial
Intelligence (AI ) Systems:
AI systems make decisions impacting our daily life Their actions might cause accidents, harm or, more generally, violate
regulations either intentionally or not and consequently might be considered suspects for various events. In this lecture we explore how digital forensics can be performed for AI based systems.
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2. Outline
• Cybersecurity – a quick recap
• Overview of AI
• Security of AI systems
• AI-aided Attacks/Maliciousness
• Use of AI in CyberSecurity
• Demo
#ISSLearningFest
3. Cybersecurity – a quick recap
C
I
PRIVACY
SAFETY
A
CONFIDENTIALITY
Ensuring that information is accessible only to
those authorised to have access.
INTEGRITY
Safeguarding the
correctness and
completeness of
information and
processing methods.
AVAILABILITY
Ensuring that authorised
users have access to
information and associated
assets when required in
whatever form required
5. Artificial Intelligence (AI)
• Artificial General Intelligence
• Do anything a human can do
• Artificial Narrow Intelligence
• Computer Vision (e.g. object recognition as in face recognition)
• Speech (e.g. smart speaker)
• Natural Language Processing (e.g. sentiment analysis, machine translation)
• Self-driving car, autonomous vehicles
6. Example: Social Distancing Detector
https://landing.ai/landing-ai-creates-an-ai-tool-to-help-customers-monitor-social-distancing-in-the-workplace/
8. Example
• 20 lawyers vs LawGeex AI
• Review 5 NDAs in 4 hours.
• 3213 clauses
• Result:
Source: https://blog.lawgeex.com/ai-more-accurate-than-lawyers/
AI Lawyers
Accuracy 94% Avg 85%
Time taken
to review all
NDAs
26 seconds Avg 92
minutes
9. Singapore’s National AI Strategy
Ref: National Artificial Intelligence Strategy - Advancing our Smart Nation Journey, Summary
10. AI, Machine Learning, Deep Learning
AI
Machine
Learning
Deep
Learning
Algorithms with ability to learn without
being explicitly programmed.
• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
• Deep Neural Networks (DNN)
13. Security of AI Systems
Exploring the additional attack surface, if any, resulting from utilizing AI
#ISSLearningFest
14. Threats (illustrative)
Prepare Training
DATA
Train the Model
• Training Set Poisoning
• DNN backdoors
• Trojaned DNN
• Privacy Concerns
• Adversarial Examples
• Physical Adversarial Examples
• Reprogramming of Neural
Networks
• Model Stealing / Model Extraction
• Model Inversion
• Membership Inference Attack
Input Trained
Model Output
15. Adversarial Example (Image Classification)
Fast Gradient Sign Method (FGSM)Source: EXPLAINING AND HARNESSING ADVERSARIAL EXAMPLES
Ian J. Goodfellow, et al. ICLR 2015
Adversarial Perturbation Adversarial Example
17. Adversarial Examples …
• … affect the integrity of the ML model
• Could lead to various cybersecurity risks and corresponding business impact
such as …
#ISSLearningFest
18. Impersonation
• Adversarial Example Attack against Face Recognition System (FRS), which
could be part of an access control or surveillance system, via
“adversarial” eyeglass frame to Impersonate a target.
19. Impersonation
Impersonation of target (cont’d)
Source:
Accessorize to a Crime: Real and
Stealthy Attacks on State-of-the-Art
Face Recognition.
Mahmood Sharif, et al
Oct 2016
20. Impersonation, Dodging
• Adversarial perturbation by project
infrared dots on attacker’s face to
induce misclassification by Face
Recognition System.
• Impersonation
• Dodging
Source:
21. Safety Issues
• Autonomous vehicle may fail to “see” the stop sign because the ML-based
model misclassifies the adversarially perturbed stop sign as a speed limit
sign.
23. Transferability of Adversarial Examples
• Adversarial examples that affect one model often affect another model
trained to perform the same task, even if the 2 models have
• Different architectures
• Different training data
x
1
x0
x2
x1
xn
y
x0
25. Security will be one of the biggest challenges in deploying AI
Dawn Song
Professor
Computer Science Division
University of California, Berkeley
26. New Challenges
• “Traditional software attack vectors are still critical to address, but they do
not provide sufficient coverage in the AI/ML threat landscape.”
• “The tech industry must avoid fighting next-gen issues with last-gen solutions
by building new frameworks and adopting new approaches which address
gaps in the design and operation of AI/ML-based services.”
Source: Securing the Future of Artificial Intelligence and Machine Learning at Microsoft
27. • Meanwhile, the following slide provides additional food for thought in this
area…
28. Protecting AI Initiatives
• How are we protecting our AI-based products, tools, and services?
• How do we keep our training data pristine and protect against biased inputs and poisoning?
• How do we protect the algorithms (or their implementation)?
• Do we have control procedures that stop abnormal events from happening and a Plan B in case we
notice that our AI programs are behaving abnormally?
• Do we have the technical and human monitoring capabilities to detect if our AI has been tampered
with?
• Have we made conscious decisions about who (or what) can decide and control which capabilities? Did
we assign AI systems an appropriate responsibility matrix entry? Do we constrain AI to decision support
or expert systems, or do we let AI programs make decisions on their own (and if so, which ones)?
• Do we have the appropriate governance policies and an agreed code of conduct that specify which of
our processes or activities are off-limits for AI for security reasons?
• When using AI in conjunction with decisions on cyber-physical systems, do we have appropriate ethical,
process, technical, and legal safeguards in place? Do we have compensating controls? How do we test
them?
• Have we aligned our cybersecurity organization, processes, policies, and technology to include AI, to
protect AI, and to protect us from AI malfunctions?
Source: https://www.bcg.com/en-sea/publications/2018/artificial-intelligence-threat-cybersecurity-solution.aspx
30. Examples
• Impersonation
• Speech synthesis systems that learn to imitate individuals’ voices
• Deepfake videos
• Generative Adversarial Network (GAN)-based tools
31. • Criminals used artificial intelligence-based software to impersonate a chief
executive’s voice and demand a fraudulent transfer of €220,000 ($243,000) in
March in what cybercrime experts described as an unusual case of artificial
intelligence being used in hacking.
• The CEO of a U.K.-based energy firm thought he was speaking on the phone
with his boss, the chief executive of the firm’s German parent company, who
asked him to send the funds to a Hungarian supplier. The caller said the request
was urgent, directing the executive to pay within an hour, according to the
company’s insurance firm, Euler Hermes Group SA.
32. Deepfake Videos
• Did Obama really say this?
Ref:
https://www.youtube.com/
watch?v=cQ54GDm1eL0
33. GAN-based tools - Examples
• MalGAN
• Generates malware that can bypass ML-based malware detectors
• PassGAN
• autonomously learn the distribution of real passwords from actual password leaks and
to generate high-quality password guesses
35. Use of AI in Cybersecurity – some examples
• Malware detection
and classification
• Spam identification
• Tier 1 analyst automation
• User and Entity Behaviour Analytics
(UEBA)
36. But it may not be robust…
DefCon AI Village (2019)
Machine Learning Static
Evasion Competition
Use hybrid approach
• AI/ML for the unknown
• Verify with tried and tested classical techniques
37. Summary
• Security will be one of the biggest challenges in deploying AI.
• New challenges require new approaches
• Malicious use of AI and AI-powered attacks must be considered as part
of an organization’s cybersecurity risk assessment.
• Consider ML-based security solutions as an augmentation (not
replacement) of your traditional security solutions and security staff.