This book lays a systematic foundation for professionals, researchers, and industry readers who are interested the applications and implications of generative AI for cybersecurity. It covers the latest advances in generative AI and its applications, risks, and opportunities in cybersecurity.
This book lays a systematic foundation for professionals, researchers, and industry readers who are interested the applications and implications of generative AI for cybersecurity. It covers the latest advances in generative AI and its applications, risks, and opportunities in cybersecurity.
Diep N. Nguyen is the Head of UTS 5G/6G Lab, Director of the Agile Communications and Computing group, Faculty of Engineering and Information Technology, University of Technology Sydney, Australia. He also holds adjunct positions at other universities in the US, Vietnam, and Japan. He received his ME and Ph.D from the University of California San Diego and The University of Arizona in 2008 and 2013, respectively. Ly T Vu is a Lecturer of at Le Quy Don Technical University (LQDTU). She received her BE and MS degrees from LQDTU, Vietnam, and Inha University, Korea, in 2011 and 2014, respectively. She received her PhD degrees from LQDTU, Vietnam, and University Technology of Sydney, Australia, in 2020 and 2024, respectively. Quang Uy Nguyen is Deputy Head of the Computer Science Department and Director of the Intelligent Computing Research Group at Le Quy Don Technical University. He obtained his BSc, MSc, and PhD in 2004, 2007, and 2011, respectively. He is a member of IEEE. Dinh Thai Hoang is an Associate Professor at University of Technology Sydney. He attained his PhD from the School of Computer Science and Engineering, Nanyang Technological University, Singapore, in 2016. He was listed among the World's Top 2% Scientists by Stanford University from 2020 to 2024.
Inhaltsangabe
PART I Fundamental Background 1. Generative AI and Its Related Components 2. Cybersecurity Fundamental: Threats, Impacts, and Countermeasures 3. Generative AI as Potential Solutions and Risks to Cybersecurity PART II Applications of Generative AI for Cybersecurity 4. Representation Learning-based Generative AI in Cybersecurity 5. Generative AI for Data Synthesis in Cybersecurity 6. Generative AI for Sequence Learning in Cybersecurity 7. Generative AI for Adversarial Learning in Cybersecurity 8. Case Studies and Detailed Implementation/Experiments PART III Conclusion and Future Perspectives 9. Emerging Topics of Generative AI in Cybersecurity 10. Future Directions and Open Challenges
PART I Fundamental Background 1. Generative AI and Its Related Components 2. Cybersecurity Fundamental: Threats, Impacts, and Countermeasures 3. Generative AI as Potential Solutions and Risks to Cybersecurity PART II Applications of Generative AI for Cybersecurity 4. Representation Learning-based Generative AI in Cybersecurity 5. Generative AI for Data Synthesis in Cybersecurity 6. Generative AI for Sequence Learning in Cybersecurity 7. Generative AI for Adversarial Learning in Cybersecurity 8. Case Studies and Detailed Implementation/Experiments PART III Conclusion and Future Perspectives 9. Emerging Topics of Generative AI in Cybersecurity 10. Future Directions and Open Challenges
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