Adversarial Intelligence: Secrecy, Privacy, and Robustness
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Multidisciplinary Applications".
Deadline for manuscript submissions: closed (18 February 2022) | Viewed by 11619
Special Issue Editors
Interests: physical-layer security; adversarial reinforcement learning; data privacy; game theory; statistical inference
Interests: machine learning; data mining; adversarial attacks; IoT security; complex network analysis
Interests: capacity of wireless networks; private/secure/coded/distributed storage/retrieval/computation; network coding; network information theory; quantum information theory
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Special Issue Information
Dear Colleagues,
Intelligent systems have been widely deployed and have significantly improved the efficiency of communication, transportation, robots, energy systems, etc. Powerful intelligence relies on a great amount of high-quality data, which however can be attacked or maliciously exploited and results in variant adversarial problems.
Research on adversarial intelligence has attracted more attention recently. In addition to improving intelligence, the design of adversarial intelligent systems also considers security, privacy, and robustness issues against active or passive attacks. Theoretic studies on the modeling, assessment, and fundamental bound of adversarial intelligent systems can be made from information-theoretic security, physical-layer security, differential privacy, or game theory. From a practice aspect, adversarial learning algorithms can be developed to improve security, privacy, or robustness. Furthermore, the adversarial problems of emerging applications, e.g., blockchain, need to be addressed.
This Special Issue will accept unpublished original papers and comprehensive reviews focused on (but not restricted to) the following research areas:
- Information theoretic security
- Communication and physical-layer security
- Data privacy and anonymity
- Game theoretic modeling of attacks
- Adversarial learning
- Security of cyberphysical systems
- Blockchain security and privacy
- Secure emerging applications
Dr. Zuxing Li
Dr. Milos Radovanovic
Prof. Dr. Syed A. Jafar
Guest Editors
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Keywords
- secure intelligent system
- assessment of secure intelligent systems
- secure scheme of intelligent systems
- physical-layer security
- data privacy
- adversarial learning
- secure emerging applications
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