1.

Record Nr.

UNINA9910770274903321

Autore

Pan Zhixin

Titolo

Explainable AI for Cybersecurity / / by Zhixin Pan, Prabhat Mishra

Pubbl/distr/stampa

Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023

ISBN

9783031464799

3031464796

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (249 pages)

Altri autori (Persone)

MishraPrabhat

Disciplina

005.8

Soggetti

Computational intelligence

Electronic circuits

Data protection

Electronic circuit design

Embedded computer systems

Artificial intelligence

Computational Intelligence

Electronic Circuits and Systems

Data and Information Security

Electronics Design and Verification

Embedded Systems

Artificial Intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Part 1: Introduction -- Chapter 1. Cybersecurity Landscape for Computer Systems -- Chapter 2. Explainable Artificial Intelligence -- Part 2: Detection of Software Vulnerabilities -- Chapter 3. Malware Detection using Explainable AI -- Chapter 4. Spectre and Meltdown Detection using Explainable AI -- Part 3: Detection of Hardware Vulnerabilities -- Chapter 5. Hardware Trojan Detection using Reinforcement Learning -- Chapter 6. Hardware Trojan Detection using Side-Channel Analysis -- Chapter 7. Hardware Trojan Detection using Shapley Ensemble Boosting -- Part 4: Mitigation of AI Vulnerabilities -- Chapter 8. Mitigation of Adversarial Machine Learning -- Chapter 9. AI Trojan Attacks and Countermeasures -- Part 5: Acceleration of



Explainable AI -- Chapter 10. Hardware Acceleration of Explainable AI -- Chapter 11. Explainable AI Acceleration using Tensor Processing Units -- Part 6: Conclusion -- Chapter 12. The Future of AI-Enabled Cybersecurity.

Sommario/riassunto

This book provides a comprehensive overview of security vulnerabilities and state-of-the-art countermeasures using explainable artificial intelligence (AI). Specifically, it describes how explainable AI can be effectively used for detection and mitigation of hardware vulnerabilities (e.g., hardware Trojans) as well as software attacks (e.g., malware and ransomware). It provides insights into the security threats towards machine learning models and presents effective countermeasures. It also explores hardware acceleration of explainable AI algorithms. The reader will be able to comprehend a complete picture of cybersecurity challenges and how to detect them using explainable AI. This book serves as a single source of reference for students, researchers, engineers, and practitioners for designing secure and trustworthy systems. Introduces a wide variety of software and hardware vulnerabilities; Describes solutions for detecting security attacks using explainable AI; Presents a fast and robust framework using hardware acceleration and mitigation of adversarial attacks.