Machine Learning under Malware Attack

Know about the book -

Machine Learning under Malware Attack is written by Raphael Labaca-Castro and published by Springer Nature. It's available with International Standard Book Number or ISBN identification 3658404426 (ISBN 10) and 9783658404420 (ISBN 13).

Machine learning has become key in supporting decision-making processes across a wide array of applications, ranging from autonomous vehicles to malware detection. However, while highly accurate, these algorithms have been shown to exhibit vulnerabilities, in which they could be deceived to return preferred predictions. Therefore, carefully crafted adversarial objects may impact the trust of machine learning systems compromising the reliability of their predictions, irrespective of the field in which they are deployed. The goal of this book is to improve the understanding of adversarial attacks, particularly in the malware context, and leverage the knowledge to explore defenses against adaptive adversaries. Furthermore, to study systemic weaknesses that can improve the resilience of machine learning models.