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Combating Cyberattacks Targeting the AI Ecosystem
Assessing Threats, Risks, and Vulnerabilities
Paperback
October 2024
9781501523243
More details
- Publisher
Mercury Learning and Information - Published
23rd October - ISBN 9781501523243
- Language English
- Pages 234 pp.
- Size 7" x 9"
$51.99
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October 2024
9781501520549
More details
- Publisher
Mercury Learning and Information - Published
10th October - ISBN 9781501520549
- Language English
- Pages 234 pp.
- Size 7" x 9"
$165.00
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October 2024
9781501520556
More details
- Publisher
Mercury Learning and Information - Published
10th October - ISBN 9781501520556
- Language English
- Pages 234 pp.
- Size 7" x 9"
$51.99
This book explores in detail the AI-driven cyber threat landscape, including inherent AI threats and risks that exist in Large Language Models (LLMs), Generative AI applications, and the AI infrastructure. The book highlights hands-on technical approaches to detect security flaws in AI systems and applications utilizing the intelligence gathered from real-world case studies. Lastly, the book presents a very detailed discussion of the defense mechanisms and practical solutions to secure
LLMs, GenAI applications, and the AI infrastructure. The chapters are structured with a granular framework, starting with AI concepts, followed by practical assessment techniques based on real-world intelligence, and concluding with required security defenses. Artificial Intelligence (AI) and cybersecurity are deeply intertwined and increasingly essential to modern
digital defense strategies. The book is a comprehensive resource for IT professionals, business leaders, and cybersecurity experts for understanding and defending against AI-driven cyberattacks.
FEATURES:
- Includes real-world case studies with detailed examples of AI-centric attacks and defense mechanisms
- Features hands-on security assessments with practical techniques for evaluating the security of AI systems
- Demonstrates advanced defense strategies with proven methods to protect LLMs, GenAI applications, and the infrastructure
Aditya K. Sood's book, Combating Cyberattacks Targeting the AI Ecosystem: Assessing Threats, Risks, and Vulnerabilities, addresses the pressing security challenges unique to AI systems. As AI becomes increasingly integrated into various sectors, it becomes a prime target for sophisticated cyber threats. Sood explores the vulnerabilities within the AI ecosystem, mainly how attackers exploit weaknesses in large language models (LLMs), generative AI (GenAI) applications, and AI infrastructure. This highlights the critical need for proactive security measures. The book offers technical insights and real-world case studies, making it an essential guide for security professionals who aim to protect AI assets. Sood stresses the importance of developing strong and adaptive defenses, detailing methods for detecting and mitigating adversarial tactics, data poisoning, and model tampering. By discussing practical strategies and forward-looking security frameworks Combating Cyberattacks Targeting the AI Ecosystem equips readers with the tools to anticipate and counter emerging AI-specific threats, presenting a valuable resource in the field of cybersecurity and preparing them for future challenges.
Renuka Nadkarni, Chief Product Officer, Aryaka
1: Introduction to AI: LLMs, GenAI Applications and the AI Infrastructure
2: The AI Trust, Compliance, and Security
3: AI Threat Landscape: Dissecting the Risks and Attack Vectors
4: Threats and Attacks Targeting the AI Ecosystem: Real-world Case Studies
5: Security Assessment of LLMs, GenAI Applications, and the AI Infrastructure
6: Defending LLMs, GenAI Applications, and the AI Infrastructure Against Cyberattacks
Appendix: Machine Learning / AI terms
Index
Aditya K. Sood, PhD
Aditya K. Sood (PhD) is a cybersecurity practitioner with more than 16 years of experience working with cross-functional teams, management, and customers to create the best-of-breed information security experience. His articles have appeared in magazines and journals, including IEEE, Elsevier, ISACA, Virus Bulletin, and USENIX. He is the author of Empirical Cloud Security 2/E (Mercury Learning) and Targeted Cyber Attacks (Syngress). He has presented his research at industry leading security conferences such as Black Hat, RSA, APWG, DEFCON, Virus Bulletin, and others.
AI Cybersecurity; Large Language Models (LLMs); Generative AI Security; AI Infrastructure Protection; AI Threat Detection; AI-driven Cyberattacks; Cyber Defense for AI; AI Risk Mitigation; AI Security Solutions