Hacking Artificial Intelligence

Davey Gibian

doi:10.5771/9781538155097

Hacking Artificial Intelligence

A Leader's Guide from Deepfakes to Breaking Deep Learning

Erschienen 2022

Kein Zugriff

doi.org/10.5771/9781538155097
ISBN print: 978-1-5381-5508-0
ISBN online: 978-1-5381-5509-7
Rowman & Littlefield, Lanham Rowman & Littlefield, Lanham

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Zusammenfassung

Sheds light on the ability to hack AI and the technology industry’s lack of effort to secure vulnerabilities.

We are accelerating towards the automated future. But this new future brings new risks. It is no surprise that after years of development and recent breakthroughs, artificial intelligence is rapidly transforming businesses, consumer electronics, and the national security landscape. But like all digital technologies, AI can fail and be left vulnerable to hacking. The ability to hack AI and the technology industry’s lack of effort to secure it is thought by experts to be the biggest unaddressed technology issue of our time. Hacking Artificial Intelligence sheds light on these hacking risks, explaining them to those who can make a difference.

Today, very few people—including those in influential business and government positions—are aware of the new risks that accompany automated systems. While society hurdles ahead with AI, we are also rushing towards a security and safety nightmare. This book is the first-ever layman’s guide to the new world of hacking AI and introduces the field to thousands of readers who should be aware of these risks. From a security perspective, AI is today where the internet was 30 years ago. It is wide open and can be exploited. Readers from leaders to AI enthusiasts and practitioners alike are shown how AI hacking is a real risk to organizations and are provided with a framework to assess such risks, before problems arise.

Schlagworte

Social Media Bots Google Software technology Apple Amazon Twitter Cybersecurity Machine Learning Microsoft Alexa AI Hacking Digital technology facial recognition computers national security Siri Elon Musk Jeff Bezos AI risk minimizing risk technology industry Kill Chains flaws of AI electronics cyberattacks data bias data poisoning data scientists developers

Keywords

Artificial Intelligence government machines

Kapitel Ausklappen | EinklappenSeiten
Preface
- Contents
1–10 Introduction 1–10
11–18 Chapter One A Brief Overview of Artificial Intelligence 11–18
19–24 Chapter Two How AI Is Different from Traditional Software 19–24
25–40 Chapter Three Data Bias 25–40
41–48 Chapter Four Hacking AI Systems 41–48
49–70 Chapter Five Evasion Attacks 49–70
71–84 Chapter Six Data Poisoning 71–84
85–94 Chapter Seven Model Inversion (“Privacy”) Attacks 85–94
95–98 Chapter Eight Obfuscation Attacks 95–98
99–108 Chapter Nine Talking to AI: Model Interpretability 99–108
109–114 Chapter Ten Machine versus Machine 109–114
115–128 Chapter Eleven Will Someone Hack My AI? 115–128
129–152 Chapter Twelve The Machine Told Us to Do It 129–152
153–158 Notes 153–158
159–168 Bibliography 159–168
169–178 Index 169–178
179–182 About the Author 179–182

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