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Essential Reading
KEVIN SCOTT, Chief Technology Officer, Microsoft
Timely
MILES BRUNDAGE, Head of Policy Research, OpenAI
Brilliant
VIJAY BOLINA, Chief Information Security Officer, DeepMind
Must Read
SVEN KRASSER, Senior Vice President and Chief Scientist, Crowdstrike
A Rare Inside Look
JANELLE SHANE, author of You Look Like A Thing And I Love You: How AI Works and Why It’s Making The World A Weirder Place
About the Book
A robust and engaging account of the single greatest threat faced by AI and ML systems
In Not With A Bug, But With A Sticker: Attacks on Machine Learning Systems and What To Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour – from inside secretive government organizations to academic workshops at ski chalets to Google’s cafeteria – recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes.
Based on hundreds of interviews of academic researchers, policy makers, business leaders and national security experts, the authors compile the complex science of attacking AI systems with color and flourish and provide a front row seat to those who championed this change. Grounded in real world examples of previous attacks, you will learn how adversaries can upend the reliability of otherwise robust AI systems with straightforward exploits.
The steeplechase to solve this problem has already begun: Nations and organizations are aware that securing AI systems brings forth an indomitable advantage: the prize is not just to keep AI systems safe but also the ability to disrupt the competition’s AI systems.
An essential and eye-opening resource for machine learning and software engineers, policy makers and business leaders involved with artificial intelligence, and academics studying topics including cybersecurity and computer science, Not With A Bug, But With A Sticker is a warning―albeit an entertaining and engaging one―we should all heed.
How we secure our AI systems will define the next decade. The stakes have never been higher, and public attention and debate on the issue has never been scarcer.
More Praise For Book
“A reality of the digital age is that every innovation contains security risk, and every security risk attracts an attacker. Ram Shankar Siva Kumar and Hyrum Anderson fire a much-needed warning flare in NOT WITH A BUG, BUT WITH A STICKER: we over-trust artificial intelligence at our peril. Every leader and policy-maker should read this compelling and persuasive book.” --- NATE FICK, New York Times bestselling author, and former CEO of the cybersecurity firm Endgame
“The intersection of technology and national security has always been a story of tension between attack and defense. With AI, the speed of attack has accelerated dramatically, while defense has not kept pace. This excellent, lively analysis shows how AI's limitations and vulnerabilities can jeopardize national security. Most importantly, Siva Kumar and Anderson provide concrete, feasible recommendations for taking steps today to bolster defenses against the certainty of pervasive adversarial AI attacks” -- LT GEN JOHN (JACK) N.T. SHANAHANUSAF (Ret.); Inaugural Director, U.S. Department of Defense Joint AI Center (JAIC)
“This is such a timely and readable book - the authors do a fantastic job of explaining complex topics and modern research in plain language with plenty of references for further exploration. AI and ML have immense utility and potential and it’s critical for security teams, builders, and operators to understand the sharp edges and pitfalls along with the benefits." – JASON CHAN, Former Information Security Leader, Netflix
""Not with a Bug" is an informative, engaging, and fun foray into how AI can be easily fooled. An excellent read for both technical and non technical readers, the authors provide a global perspective on what's happening today, but also empowers the reader with tools to make informed decisions that impact tomorrow." --- DR. RUMMAN CHOWDHURY, Director, ML Ethics, Transparency and Accountability, Twitter
“As AI becomes infused into all computer systems, from social networks to business, critical infrastructure and defense systems, the security of those systems depends on the security of the AI they use. This book presents the unique risks and considerations of AI with engaging stories and insightful examples. It is a wakeup call to security professionals and organizations adopting and developing AI.” --- MARK RUSSINOVICH, Azure CTO and Technical Fellow, Microsoft
“Siva Kumar and Anderson take you on a wild ride uncovering the victories and triumphs of AI/ML. This should be required reading to become AI/ML literate in the field.” --- DAVID BRUMLEY, Professor of ECE and CS, Carnegie Mellon University
"Trust, in ways both good and bad, is emerging as a critical aspect of the relationships we are coming to have with AI. Not With a Bang, But With a Sticker is an eye-opening book that will change the way you think about the systems that pervade our world—and its lessons should be taken to heart by all who build them." --- BRIAN CHRISTIAN, author of The Alignment Problem
"At last -- and not a moment too soon -- a book that in plain language describes the distinct and deep issues of securing now-ubiquitous machine learning tools. Whether you're looking to deploy them in your own domain, or simply among the billions of people now subject to them, this is a vital read." --- JONATHAN ZITTRAIN - George Bemis Professor of International Law and Professor of Computer Science, Harvard University
“We are fast entering a world of powerful but brittle AI systems, one where failures can result in catastrophic consequences. Siva Kumar and Anderson have written an essential guide for understanding the unique – and troubling – failure modes of AI systems today. Through easily accessible examples and anecdotes, they break down the problems of machine learning systems and how society can address them to build a safer world” - PAUL SCHARRE, author of Four Battlegrounds and Army of None
Essential Reading ◦ Chief Technology Officer, Microsoft
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Brilliant - Chief Information Security Officer, DeepMind
〰️
Timely - Head of Policy Research, OpenAI
〰️
Must Read - Senior Vice President and Chief Scientist, Crowdstrike
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A Rare Inside Look - Author
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Essential Reading ◦ Chief Technology Officer, Microsoft 〰️ Brilliant - Chief Information Security Officer, DeepMind 〰️ Timely - Head of Policy Research, OpenAI 〰️ Must Read - Senior Vice President and Chief Scientist, Crowdstrike 〰️ A Rare Inside Look - Author 〰️
A robust and engaging account of the single greatest threat faced by AI and ML systems
A riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats.
Based on hundreds of interviews of academic researchers, policy makers, business leaders and national security experts
Grounded in real-world examples of previous attacks, you will learn how adversaries can upend the reliability of otherwise robust AI systems
All proceeds from this book to two charities: Black in AI and Bountiful Children’s Foundation
Essential Reading
Kevin Scott, Chief Technology Officer, Microsoft
Timely
Miles Brundage, Head of Policy Research, OpenAI
Brilliant
Vijay Bolina, Chief Information Security Officer, DeepMind
Must Read
Sven Krasser, Senior Vice President and Chief Scientist, Crowdstrike
A Rare Inside Look
Janelle Shane, author of You Look Like A Thing And I Love You: How AI Works and Why It’s Making The World A Weirder Place
Ram Shankar Siva Kumar
Ram is a Data Cowboy in Azure Security at Microsoft, working in the intersection of Machine Learning and Security. At Microsoft, his primary focus is modeling massive amounts of security logs to surface malicious activity. For instance, how do you detect an attacker is moving through the system when you have to analyze billions of events per second?
Another area of focus, is the use of machine learning systems for offense - for instance, what does automatic attack planning and automatic attack execution look in the context of red teaming? His work has appeared in industry conferences like BlueHat, DerbyCon, MIRCon, Infiltrate, Strata+Hadoop World Practice of Machine Learning as well as academic conferences like NIPS, IEEE Usenix, ACM - CCS.