Beyond the Algorithm: AI, Security, Privacy, and Ethics

This book is a comprehensive, cutting-edge guide designed to educate readers on the essentials of artificial intelligence (AI) and machine learning (ML), while emphasising the crucial aspects of security, ethics, and privacy. The book aims to equip AI practitioners, IT professionals, data scientists, security experts, policy-makers, and students with the knowledge and tools needed to develop, deploy, and manage AI and ML systems securely and responsibly. Samples Preview sample pages from Beyond the Algorithm: AI, Security, Privacy, and Ethics > The book is divided into several sections, each focusing on a specific aspect of AI. It begins by introducing the fundamentals of AI technologies, providing an overview of their history, development, and various types. This is followed by a deep dive into popular AI algorithms and large language models (LLMs), including GPT-4, that are at the forefront of AI innovation. Next, the book explores the critical security aspects of AI systems, examining the importance of security and the key challenges faced in this domain. It also delves into the common threats, vulnerabilities, and attack vectors, as well as risk assessment and management strategies. This manuscript covers data security, model security, system and infrastructure security, secure development practices, monitoring and auditing, supply chain security, and secure deployment and maintenance. Another key focus of the book is privacy and ethical considerations in AI systems. Topics covered include bias and fairness, transparency and accountability, and privacy and data protection. The book also addresses legal and regulatory compliance, providing an overview of relevant regulations and guidelines, and discussing how to ensure compliance in AI systems through case studies and best practices.

Table of Contents:
1 Historical Overview of Artificial Intelligence (AI) and Machine Learning (ML) 2 Fundamentals of AI and ML Technologies and Implementations 3 Generative AI and Large Language Models 4 The Cornerstones of AI and ML Security 5 Hacking AI Systems 6 System and Infrastructure Security 7 Privacy and Ethics: Navigating Privacy and Ethics in an AI-Infused World 8 Legal and Regulatory Compliance for AI Systems Test Your Skills Answers and Solutions

About the Author :
Omar Santos is a cybersecurity thought leader with a passion for driving industry-wide initiatives to enhance the security of critical infrastructures. Omar is the lead of the DEF CON Red Team Village, the chair of the Common Security Advisory Framework (CSAF) technical committee, the founder of OpenEoX, and board member of the OASIS Open standards organisation. Omar is a renowned expert in ethical hacking, vulnerability research, incident response, and AI security. He employs his deep understanding of these disciplines to help organisations stay ahead of emerging threats. His dedication to cybersecurity has made a significant impact on businesses, academic institutions, law enforcement agencies, and other entities striving to bolster their security measures. With more than 20 books, video courses, white papers, and technical articles under his belt, Omar's expertise is widely recognised and respected. Omar is a Distinguished Engineer at Cisco focusing on AI security, research, incident response, and vulnerability disclosure. Petar Radanliev is a Postdoctoral Research Associate at the Department of Computer Science at the University of Oxford. He obtained his PhD at the University of Wales in 2014. He continued with postdoctoral research at Imperial College London, the University of Cambridge, Massachusetts Institute of Technology, and the Department of Engineering Science at the University of Oxford before moving to the Department of Computer Science. His current research focuses on artificial intelligence, cybersecurity, quantum computing, and blockchain technology.