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AI embedded assurance for cyber systems

Wang, Cliff.

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AI embedded assurance for cyber systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	AI embedded assurance for cyber systems/ edited by Cliff Wang, S.S. Iyengar, Kun Sun.
other author:	Wang, Cliff.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	xvii, 246 p. :ill., digital ;24 cm.
[NT 15003449]:	Part. I. AI/ML for Digital Forensics -- Chapter. 1. Writer-dependent Off-line Signature Verification with Neural Networks -- Chapter. 2. Political Activism and Technology -- Chapter. 3. Forensic Proof and Criminal Liability for Development, Distribution and Use of Artificial Intelligence -- Part. II. AI/ML for CPS -- Chapter. 4. Automotive Batteries as Anomaly Detectors -- Chapter. 5. Zero Trust Architecture For Cyber-Physical Power System Security Based on Machine Learning -- Chapter. 6. AI-enabled Real-time Sensor Attack Detection for Cyber-physical Systems -- Part. III. AI/ML for Cyber Analysis -- Chapter. 7. Generating Vulnerable Code via Learning-Based Program Transformation -- Chapter. 8. Security and Privacy Problems in Self-Supervised Learning -- Chapter. 9. Federated Learning for IoT Applications, Attacks and Defense Methods -- Chapter. 10. AI Powered Correlation Technique to Detect Virtual Machine Attacks in Private Cloud Environment -- Chapter. 11. Detecting Fake Users in Online Social Networks -- Chapter. 12. Explaining Deep Learning based Security Applications -- Glossary -- Index.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence. -
Online resource:	https://doi.org/10.1007/978-3-031-42637-7
ISBN:	9783031426377

AI embedded assurance for cyber systems
AI embedded assurance for cyber systems[electronic resource] /edited by Cliff Wang, S.S. Iyengar, Kun Sun. - Cham :Springer International Publishing :2023. - xvii, 246 p. :ill., digital ;24 cm.

Part. I. AI/ML for Digital Forensics -- Chapter. 1. Writer-dependent Off-line Signature Verification with Neural Networks -- Chapter. 2. Political Activism and Technology -- Chapter. 3. Forensic Proof and Criminal Liability for Development, Distribution and Use of Artificial Intelligence -- Part. II. AI/ML for CPS -- Chapter. 4. Automotive Batteries as Anomaly Detectors -- Chapter. 5. Zero Trust Architecture For Cyber-Physical Power System Security Based on Machine Learning -- Chapter. 6. AI-enabled Real-time Sensor Attack Detection for Cyber-physical Systems -- Part. III. AI/ML for Cyber Analysis -- Chapter. 7. Generating Vulnerable Code via Learning-Based Program Transformation -- Chapter. 8. Security and Privacy Problems in Self-Supervised Learning -- Chapter. 9. Federated Learning for IoT Applications, Attacks and Defense Methods -- Chapter. 10. AI Powered Correlation Technique to Detect Virtual Machine Attacks in Private Cloud Environment -- Chapter. 11. Detecting Fake Users in Online Social Networks -- Chapter. 12. Explaining Deep Learning based Security Applications -- Glossary -- Index.

The rapid growth and reliance on cyber systems have permeated our society, government, and military which is demonstrated in this book. The authors discuss how AI-powered cyber systems are designed to protect against cyber threats and ensure the security and reliability of digital systems using artificial intelligence (AI) technologies. As AI becomes more integrated into various aspects of our lives, the need for reliable and trustworthy AI systems becomes increasingly important. This book is an introduction to all of the above-mentioned areas in the context of AI Embedded Assurance for Cyber Systems. This book has three themes. First, the AI/ML for digital forensics theme focuses on developing AI and ML powered forensic tools, techniques, software, and hardware. Second, the AI/ML for cyber physical system theme describes that AI/ML plays an enabling role to boost the development of cyber physical systems (CPS), especially in strengthening the security and privacy of CPS. Third, the AI/ML for cyber analysis theme focuses on using AI/ML to analyze tons of data in a timely manner and identify many complex threat patterns. This book is designed for undergraduates, graduate students in computer science and researchers in an interdisciplinary area of cyber forensics and AI embedded security applications. It is also useful for practitioners who would like to adopt AIs to solve cyber security problems.

ISBN: 9783031426377

Standard No.: 10.1007/978-3-031-42637-7doiSubjects--Topical Terms:

516317
Artificial intelligence.

LC Class. No.: Q335

Dewey Class. No.: 006.3

AI embedded assurance for cyber systems
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505 0 $a Part. I. AI/ML for Digital Forensics -- Chapter. 1. Writer-dependent Off-line Signature Verification with Neural Networks -- Chapter. 2. Political Activism and Technology -- Chapter. 3. Forensic Proof and Criminal Liability for Development, Distribution and Use of Artificial Intelligence -- Part. II. AI/ML for CPS -- Chapter. 4. Automotive Batteries as Anomaly Detectors -- Chapter. 5. Zero Trust Architecture For Cyber-Physical Power System Security Based on Machine Learning -- Chapter. 6. AI-enabled Real-time Sensor Attack Detection for Cyber-physical Systems -- Part. III. AI/ML for Cyber Analysis -- Chapter. 7. Generating Vulnerable Code via Learning-Based Program Transformation -- Chapter. 8. Security and Privacy Problems in Self-Supervised Learning -- Chapter. 9. Federated Learning for IoT Applications, Attacks and Defense Methods -- Chapter. 10. AI Powered Correlation Technique to Detect Virtual Machine Attacks in Private Cloud Environment -- Chapter. 11. Detecting Fake Users in Online Social Networks -- Chapter. 12. Explaining Deep Learning based Security Applications -- Glossary -- Index.
520 $a The rapid growth and reliance on cyber systems have permeated our society, government, and military which is demonstrated in this book. The authors discuss how AI-powered cyber systems are designed to protect against cyber threats and ensure the security and reliability of digital systems using artificial intelligence (AI) technologies. As AI becomes more integrated into various aspects of our lives, the need for reliable and trustworthy AI systems becomes increasingly important. This book is an introduction to all of the above-mentioned areas in the context of AI Embedded Assurance for Cyber Systems. This book has three themes. First, the AI/ML for digital forensics theme focuses on developing AI and ML powered forensic tools, techniques, software, and hardware. Second, the AI/ML for cyber physical system theme describes that AI/ML plays an enabling role to boost the development of cyber physical systems (CPS), especially in strengthening the security and privacy of CPS. Third, the AI/ML for cyber analysis theme focuses on using AI/ML to analyze tons of data in a timely manner and identify many complex threat patterns. This book is designed for undergraduates, graduate students in computer science and researchers in an interdisciplinary area of cyber forensics and AI embedded security applications. It is also useful for practitioners who would like to adopt AIs to solve cyber security problems.
650 0 $a Artificial intelligence. $3 516317
650 0 $a Machine learning. $3 533906
650 0 $a Cooperating objects (Computer systems) $x Security measures. $3 2200529
650 0 $a Digital forensic science. $3 3338165
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Mobile and Network Security. $3 3382377
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Computer Crime. $3 3382518
650 2 4 $a Cybercrime. $3 2195714
650 2 4 $a Cyber-Physical Systems. $3 3591993
700 1 $a Wang, Cliff. $3 898853
700 1 $a Iyengar, S. S. $3 896740
700 1 $a Sun, Kun. $3 3634675
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-42637-7
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)