AI, Machine Learning and Deep Learning : A Security Perspective /: A Security Perspective. (2023)
- Record Type:
- Book
- Title:
- AI, Machine Learning and Deep Learning : A Security Perspective /: A Security Perspective. (2023)
- Main Title:
- AI, Machine Learning and Deep Learning : A Security Perspective
- Further Information:
- Note: Fei Hu, Xiali Hei.
- Editors:
- Hu, Fei
Hei, Xiali - Contents:
- Part I. Secure AI/ML Systems: Attack Models 1. Machine Learning Attack Models by Jing Lin, Long Dang, Mohamed Rahouti, Kaiqi Xiong. 2. Adversarial Machine Learning: A New Threat Paradigm for Next-Generation Wireless Communications by Yalin E. Sagduyu, Yi Shi, Tugba Erpek, William Headley, Bryse Flowers, George Stantchev, Zhuo Lu, and Brian Jalaian. 3. Threat of Adversarial Attacks to Deep Learning: A survey by Linsheng He, Fei Hu. 4. Attack Models for Collaborative Deep Learning by Jiamiao Zhao, Fei Hu, Xiali Hei. 5. Attacks on Deep Reinforcement Learning Systems: A Tutorial by Joseph Layton Fei Hu. 6. Trust and Security of Deep Reinforcement Learning by Yen-Hung Chen, Mu-Tien Huang, and Yuh-Jong Hu. 7. IoT threat modeling using Bayesian networks by Diego Heredia. Part II. Secure AI/ML Systems: Defenses 8. Survey of Machine Learning Defense Strategies by Joseph Layton, Fei Hu, Xiali Hei. 9. Defenses to Deep Learning Attacks by Linsheng He, Fei Hu. 10. Defensive Schemes for Cyber Security of Deep Reinforcement Learning by Jiamiao Zhao, Fei Hu, Xiali Hei. 11. Adversarial Attacks on Machine Learning models in Cyber Physical System by Mahbub Rahman, Fei Hu. 12. Federated learning and Blockchain: An opportunity for Artificial Intelligence with data regulation by Darine Amayed, Fehmi Jaafar, Riadh Ben Chaabene, and Mohamed Cheriet. Part III. Use AI/ML Algorithms for Cyber Security 13. Use Machine learning for Cyber Security: Overview by Dr. D. Roshni Thanka, Dr. G. Jaspher W.Part I. Secure AI/ML Systems: Attack Models 1. Machine Learning Attack Models by Jing Lin, Long Dang, Mohamed Rahouti, Kaiqi Xiong. 2. Adversarial Machine Learning: A New Threat Paradigm for Next-Generation Wireless Communications by Yalin E. Sagduyu, Yi Shi, Tugba Erpek, William Headley, Bryse Flowers, George Stantchev, Zhuo Lu, and Brian Jalaian. 3. Threat of Adversarial Attacks to Deep Learning: A survey by Linsheng He, Fei Hu. 4. Attack Models for Collaborative Deep Learning by Jiamiao Zhao, Fei Hu, Xiali Hei. 5. Attacks on Deep Reinforcement Learning Systems: A Tutorial by Joseph Layton Fei Hu. 6. Trust and Security of Deep Reinforcement Learning by Yen-Hung Chen, Mu-Tien Huang, and Yuh-Jong Hu. 7. IoT threat modeling using Bayesian networks by Diego Heredia. Part II. Secure AI/ML Systems: Defenses 8. Survey of Machine Learning Defense Strategies by Joseph Layton, Fei Hu, Xiali Hei. 9. Defenses to Deep Learning Attacks by Linsheng He, Fei Hu. 10. Defensive Schemes for Cyber Security of Deep Reinforcement Learning by Jiamiao Zhao, Fei Hu, Xiali Hei. 11. Adversarial Attacks on Machine Learning models in Cyber Physical System by Mahbub Rahman, Fei Hu. 12. Federated learning and Blockchain: An opportunity for Artificial Intelligence with data regulation by Darine Amayed, Fehmi Jaafar, Riadh Ben Chaabene, and Mohamed Cheriet. Part III. Use AI/ML Algorithms for Cyber Security 13. Use Machine learning for Cyber Security: Overview by Dr. D. Roshni Thanka, Dr. G. Jaspher W. Kathrine, Dr. E. Bijolin Edwin. 14. Performance of Machine Learning and Big Data Analytics paradigms in Cybersecurity by Gabriel Kabanda. 15. Using ML and DL algorithms for Intrusion Detection in Industrial Internet of Things by Nicole do Vale Dalarmelina, Pallavi Arora, Baljeet Kaur, Rodolfo Ipolito Meneguette, Marcio Andrey Teixeira. Part IV. Applications 16. On Detecting Interest Flooding Attacks in Named Data Networking (NDN) based IoT Search by Hengshuo Liang, Lauren Burgess, Weixian Liao, Qianlong Wang, and Wei Yu . 17. Attack on fraud detection system in online banking using generative adversarial networks by Jerzy Surma, Krzysztof Jagiełło. 18. An Artificial Intelligence-Assisted Security Analysis of Smart Healthcare Systems by Nur Imtiazul Haque and Mohammad Ashiqur Rahman. 19. A User-Centric Focus for Detecting Phishing Emails by Regina Eckhardt and Sikha Bagui. … (more)
- Edition:
- 1st
- Publisher Details:
- CRC Press
- Publication Date:
- 2023
- Extent:
- 1 online resource (334 pages), (5 illustrations)
- Languages:
- English
- ISBNs:
- 9781000878899
1000878899 - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.763426
- Ingest File:
- 18_057.xml