DESCRIPTION In an age where data breaches and privacy issues are growing, confidential computing offers a state-of-the-art solution. This technology helps organizations keep their most sensitive information safe, even against strong threats. Introduction to Confidential Computing provides a clear guide to this advanced cybersecurity technology. It explains why confidential computing is crucial for protecting sensitive data, covering key technologies, architectures, and frameworks. The book details remote attestation, which ensures computing environment integrity, and explores how confidential computing enhances AI training security. It also reviews solutions from major cloud providers, helping readers choose the right options. This book is perfect for anyone looking to boost their cybersecurity skills and stay ahead in data protection. By the end of this book, you will gain a thorough understanding of confidential computing and its impact on data security and privacy. You will be ready to assess and implement confidential computing solutions, safeguarding your organization's assets and meeting data privacy regulations. KEY FEATURES ● Comprehensive overview of confidential computing architectures and technologies. ● Guidance on leveraging confidential computing technologies for secure data processing and privacy protection. ● Learn how confidential computing ensures data privacy and protects AI model integrity through secure processing. WHAT YOU WILL LEARN ● Learn why confidential computing is crucial in today's digital world. ● Understand high-level architecture of various trusted execution environments implementations. ● Art of developing secure applications that can be deployed on TEE. ● Comprehend how remote attestation ensures the integrity of computing environments. ● Discover how RA-TLS could reshape the future of secure communications. ● Explore how confidential computing protects data and AI models. WHO THIS BOOK IS FOR This book is for software architects, security researchers, and developers to enhance application security using confidential computing. PhD candidates and postgraduates will explore TEEs, while AI/ML developers will understand how confidential AI protects data and models. TABLE OF CONTENTS 1. Vital Need for Confidential Computing 2. Trusted Execution Environments 3. Secure Application Development 4. Remote Attestation 5. Confidential Computing in Cloud 6. Confidential Artificial Intelligence 7. Prospects of Confidential Computing Appendix A: Enclave Initialization Instructions in Intel SGX Appendix B: Intel TDX Architectural Instructions Appendix C: Secure Boot Infrastructure Terminologies

This book covers the fundamental concepts of private AI and its applications. It also covers fusion of Private AI with cutting-edge technologies like cloud computing, federated learning and computer vision. Security Models and Applications for Sustainable Development Using Private AI reviews various encryption algorithms used for providing security in private AI. It discusses the role of training machine learning and Deep learning technologies in private AI. The book provides case studies of using private AI in various application areas such as purchasing, education, entertainment, medical diagnosis, predictive care, conversational personal assistants, wellness apps, early disease detection, and recommendation systems. The authors provide additional knowledge to handling the customer’s data securely and efficiently. It also provides multi-model dataset storage approaches along with the traditional approaches like anonymization of data and differential privacy mechanisms. The target audience includes undergraduate and postgraduate students in Computer Science, Information technology, Electronics and Communication Engineering and related disciplines. This book is also a one stop reference point for professionals, security researchers, scholars, various government agencies and security practitioners, and experts working in the cybersecurity Industry specifically in the R & D division.

This book examines the interconnections between artificial intelligence, data governance and private law rules with a comparative focus on selected jurisdictions in the Asia-Pacific region. The chapters discuss the myriad challenges of translating and adapting theory, doctrines and concepts to practice in the Asia-Pacific region given their differing circumstances, challenges and national interests. The contributors are legal experts from the UK, Israel, Korea, and Singapore with extensive academic and practical experience. The essays in this collection cover a wide range of topics, including data protection and governance, data trusts, information fiduciaries, medical AI, the regulation of autonomous vehicles, the use of blockchain technology in land administration, the regulation of digital assets and contract formation issues arising from AI applications. The book will be of interest to members of the judiciary, policy makers and academics who specialise in AI, data governance and/or private law or who work at the intersection of these three areas, as well as legal technologists and practising lawyers in the Asia-Pacific, the UK and the US.

In this “dishy…superbly reported” (Entertainment Weekly) New York Times bestseller, Peter Biskind chronicles the rise of independent filmmakers who reinvented Hollywood—most notably Sundance founder Robert Redford and Harvey Weinstein, who with his brother, Bob, made Miramax Films an indie powerhouse. As he did in his acclaimed Easy Riders, Raging Bulls, Peter Biskind “takes on the movie industry of the 1990s and again gets the story” (The New York Times). Biskind charts in fascinating detail the meteoric rise of the controversial Harvey Weinstein, often described as the last mogul, who created an Oscar factory that became the envy of the studios, while leaving a trail of carnage in his wake. He follows Sundance as it grew from a regional film festival to the premier showcase of independent film, succeeding almost despite the mercurial Redford, whose visionary plans were nearly thwarted by his own quixotic personality. Likewise, the directors who emerged from the independent movement, such as Quentin Tarantino, Steven Soderbergh, and David O. Russell, are now among the best-known directors in Hollywood. Not to mention the actors who emerged with them, like Matt Damon, Ben Affleck, Ethan Hawke, and Uma Thurman. Candid, controversial, and “sensationally entertaining” (Los Angeles Times) Down and Dirty Pictures is a must-read for anyone interested in the film world.

In this compulsively readable and constantly surprising book, Peter Biskind, the author of the film classics Easy Riders, Raging Bulls and Down and Dirty Pictures, writes the most intimate, revealing, and balanced biography ever of Hollywood legend Warren Beatty. Famously a playboy, Beatty has also been one of the most ambitious and successful stars in Hollywood. Several Beatty films have passed the test of time, from Bonnie and Clyde (which confirmed for him the importance of controlling the projects he was involved in) to Shampoo, Heaven Can Wait, Reds (for which he won the best director Oscar), Bugsy, and Bulworth. Few filmgoers realize that along with Orson Welles, Beatty is the only person ever nominated for four Academy Awards for a single film -- and unlike Welles, Beatty did it twice, with Heaven Can Wait and Reds. Biskind shows how Beatty used star power, commercial success, savvy, and charm to bend Hollywood moguls to his will, establishing an unprecedented level of independence while still working within the studio system. Beatty's private life has been the subject of gossip for decades, and Star confirms his status as Hollywood's leading man in the bedroom, describing his affairs with Joan Collins, Natalie Wood, Leslie Caron, Julie Christie, Michelle Phillips, Diane Keaton, and Madonna, among many others. Throughout his career, Beatty has demonstrated a fascination for politics. He was influential in the 1984 and 1988 presidential campaigns of Gary Hart. It was said of Hart and Beatty that each wanted to be the other, and Biskind shows that there was considerable truth in that wry observation. As recently as a few years ago, Beatty was speaking out about California politics and contemplating a run for governor. Biskind explains how Beatty exercised unique control, often hiring screenwriters out of his own pocket (and frequently collaborating with them), producing, directing, and acting in his own films, becoming an auteur before anyone in Hollywood knew what the word meant. He was arguably one of the most successful and creative figures in Hollywood during the second half of the twentieth century, and in this fascinating biography, Warren Beatty comes to life -- complete with excesses and achievements -- as never before.

AUTOMATED SECURE COMPUTING FOR NEXT-GENERATION SYSTEMS This book provides cutting-edge chapters on machine-empowered solutions for next-generation systems for today’s society. Security is always a primary concern for each application and sector. In the last decade, many techniques and frameworks have been suggested to improve security (data, information, and network). Due to rapid improvements in industry automation, however, systems need to be secured more quickly and efficiently. It is important to explore the best ways to incorporate the suggested solutions to improve their accuracy while reducing their learning cost. During implementation, the most difficult challenge is determining how to exploit AI and ML algorithms for improved safe service computation while maintaining the user’s privacy. The robustness of AI and deep learning, as well as the reliability and privacy of data, is an important part of modern computing. It is essential to determine the security issues of using AI to protect systems or ML-based automated intelligent systems. To enforce them in reality, privacy would have to be maintained throughout the implementation process. This book presents groundbreaking applications related to artificial intelligence and machine learning for more stable and privacy-focused computing. By reflecting on the role of machine learning in information, cyber, and data security, Automated Secure Computing for Next-Generation Systems outlines recent developments in the security domain with artificial intelligence, machine learning, and privacy-preserving methods and strategies. To make computation more secure and confidential, the book provides ways to experiment, conceptualize, and theorize about issues that include AI and machine learning for improved security and preserve privacy in next-generation-based automated and intelligent systems. Hence, this book provides a detailed description of the role of AI, ML, etc., in automated and intelligent systems used for solving critical issues in various sectors of modern society. Audience Researchers in information technology, robotics, security, privacy preservation, and data mining. The book is also suitable for postgraduate and upper-level undergraduate students.