Strengthening Deep Neural Networks - by Katy Warr (Paperback)
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<p/><br></br><p><b> About the Book </b></p></br></br>As Deep Neural Networks (DNNs) become increasingly common in real-world applications, the potential to "fool" them presents a new attack vector. Warr examines the motivations attackers have for exploiting flaws in DNN algorithms and how to assess the threat to systems incorporating neural network technology.<p/><br></br><p><b> Book Synopsis </b></p></br></br><p>As deep neural networks (DNNs) become increasingly common in real-world applications, the potential to deliberately fool them with data that wouldn't trick a human presents a new attack vector. This practical book examines real-world scenarios where DNNs--the algorithms intrinsic to much of AI--are used daily to process image, audio, and video data.</p><p>Author Katy Warr considers attack motivations, the risks posed by this adversarial input, and methods for increasing AI robustness to these attacks. If you're a data scientist developing DNN algorithms, a security architect interested in how to make AI systems more resilient to attack, or someone fascinated by the differences between artificial and biological perception, this book is for you.</p><ul><li>Delve into DNNs and discover how they could be tricked by adversarial input</li><li>Investigate methods used to generate adversarial input capable of fooling DNNs</li><li>Explore real-world scenarios and model the adversarial threat</li><li>Evaluate neural network robustness; learn methods to increase resilience of AI systems to adversarial data</li><li>Examine some ways in which AI might become better at mimicking human perception in years to come</li></ul><p/><br></br><p><b> About the Author </b></p></br></br><p>Katy Warr works at Roke Manor Research in the UK creating solutions for complex real-world problems. She specializes in AI and data analytics and leads the company's technical strategy in these areas. Previously she worked at IBM UK Laboratories, architecting and developing software for a variety of distributed enterprise products with an emphasis on transactional integrity and security.<br/><br/>Katy gained her degree in AI and Computer Science from the University of Edinburgh at a time when there was insufficient compute power and data available for deep learning to be much more than a theoretical pursuit. Fast forward a few years and she considers herself fortunate to witness this exciting field becoming mainstream.</p>
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