04751nam a22006735i 4500 978-3-031-54252-7 DE-He213 20251030111806.0 cr nn 008mamaa 240405s2024 sz | s |||| 0|eng d 9783031542527 978-3-031-54252-7 10.1007/978-3-031-54252-7 doi HF54.5-54.56 KJQ bicssc UF bicssc BUS083000 bisacsh KJQ thema UF thema Generative AI Security [electronic resource] : Theories and Practices / edited by Ken Huang, Yang Wang, Ben Goertzel, Yale Li, Sean Wright, Jyoti Ponnapalli. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XXXV, 338 p. 44 illus., 34 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Future of Business and Finance, 2662-2475 Foundations of Generative AI -- Navigating the GenAI Security -- AI Regulations -- Build Your Security Program for GenAI -- GenAI Data Security -- GenAI Model Security -- GenAI Application Level Security -- From LLMOps to DevSecOps for GenAI -- Utilizing Prompt Engineering to Operationalize Cyber Security -- Use GenAI Tools to Boost Your Security Posture. This book explores the revolutionary intersection of Generative AI (GenAI) and cybersecurity. It presents a comprehensive guide that intertwines theories and practices, aiming to equip cybersecurity professionals, CISOs, AI researchers, developers, architects and college students with an understanding of GenAI’s profound impacts on cybersecurity. The scope of the book ranges from the foundations of GenAI, including underlying principles, advanced architectures, and cutting-edge research, to specific aspects of GenAI security such as data security, model security, application-level security, and the emerging fields of LLMOps and DevSecOps. It explores AI regulations around the globe, ethical considerations, the threat landscape, and privacy preservation. Further, it assesses the transformative potential of GenAI in reshaping the cybersecurity landscape, the ethical implications of using advanced models, and the innovative strategies required to secure GenAI applications. Lastly, the book presents an in-depth analysis of the security challenges and potential solutions specific to GenAI, and a forward-looking view of how it can redefine cybersecurity practices. By addressing these topics, it provides answers to questions on how to secure GenAI applications, as well as vital support with understanding and navigating the complex and ever-evolving regulatory environments, and how to build a resilient GenAI security program. The book offers actionable insights and hands-on resources for anyone engaged in the rapidly evolving world of GenAI and cybersecurity. Business information services. Financial risk management. 59046 Data protection. Artificial intelligence. 58441 Information technology Moral and ethical aspects. 64910 IT in Business. Risk Management. 59047 Data and Information Security. 66492 Artificial Intelligence. 58441 Information Ethics. 68804 Huang, Ken. editor. (orcid)0009-0004-6502-3673 https://orcid.org/0009-0004-6502-3673 edt http://id.loc.gov/vocabulary/relators/edt 74774 Wang, Yang. editor. edt http://id.loc.gov/vocabulary/relators/edt 74775 Goertzel, Ben. editor. edt http://id.loc.gov/vocabulary/relators/edt 74776 Li, Yale. editor. edt http://id.loc.gov/vocabulary/relators/edt 74777 Wright, Sean. editor. edt http://id.loc.gov/vocabulary/relators/edt 74778 Ponnapalli, Jyoti. editor. edt http://id.loc.gov/vocabulary/relators/edt 74779 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031542510 Printed edition: 9783031542534 Printed edition: 9783031542541 Future of Business and Finance, 2662-2475 68594 https://doi.org/10.1007/978-3-031-54252-7 ZDB-2-BUM ZDB-2-SXBM 58969 58969