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Explainable AI for cybersecurity

Record Type:	Electronic resources : Monograph/item
Title/Author:	Explainable AI for cybersecurity/ by Zhixin Pan, Prabhat Mishra.
Author:	Pan, Zhixin.
other author:	Mishra, Prabhat.
Published:	Cham :Springer Nature Switzerland : : 2023.,
Description:	xviii, 243 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence - Data processing. -
Online resource:	https://doi.org/10.1007/978-3-031-46479-9
ISBN:	9783031464799

Explainable AI for cybersecurity
Pan, Zhixin.

Explainable AI for cybersecurity[electronic resource] /by Zhixin Pan, Prabhat Mishra. - Cham :Springer Nature Switzerland :2023. - xviii, 243 p. :ill. (chiefly color), digital ;24 cm.

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.

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.

ISBN: 9783031464799

Standard No.: 10.1007/978-3-031-46479-9doiSubjects--Topical Terms:

655284
Artificial intelligence
--Data processing.

LC Class. No.: Q342 / .P36 2023

Dewey Class. No.: 006.3

Explainable AI for cybersecurity
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245 1 0 $a Explainable AI for cybersecurity $h [electronic resource] / $c by Zhixin Pan, Prabhat Mishra.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2023.
300 $a xviii, 243 p. : $b ill. (chiefly color), digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
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650 0 $a Internet of things $x Security measures. $3 3217048
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650 2 4 $a Electronic Circuits and Systems. $3 3538814
650 2 4 $a Data and Information Security. $3 3538510
650 2 4 $a Electronics Design and Verification. $3 3592716
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650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Mishra, Prabhat. $3 896585
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856 4 0 $u https://doi.org/10.1007/978-3-031-46479-9
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)