Special Issues
Table of Content

Applications of Artificial Intelligence for Information Security

Submission Deadline: 30 December 2024 View: 94 Submit to Special Issue

Guest Editors

Dr. Shaozhang Niu, Beijing University of Posts and Telecommunications, China
Dr. Zhenguang Gao, Framingham State University, USA
Dr. Jiancheng Zou, North China University of Technology, China


Artificial intelligence (AI) and information security are two hot research areas today. AI is profoundly influencing and changing the patterns of our lives, work, and learning. It is widely used in various fields such as autonomous driving, medical diagnosis, and smart home, providing more accurate and efficient solutions. With the development of information technology, especially the breakthrough progress of next-generation AI technologies such as large models, information security issues are becoming increasingly prominent, and the data security of governments and enterprises and personal privacy protection are facing huge challenges. AI and information security technology are mutually penetrating, promoting, and constraining their respective development. Faced with a large number of key challenges emerging in the fields of AI and information security, researchers and technology developers are diligently working to provide proper solutions within these domains. This special issue aims to delve into the evolving landscape of AI and security concerns.  We invite academic and industrial communities to present their cutting-edge research, offering innovative solutions to meet these challenges. Together, let's embrace the AI promising future, fortify against various security threats, and unlock boundless opportunities.


Machine learning algorithms.
Natural language processing (NLP).
Computer vision and pattern recognition.
Reinforcement learning.
Deep learning.
Explainable AI.
AI ethics and fairness.
Knowledge representation and reasoning.
AI in healthcare.
Threat detection and prevention.
Anomaly detection.
Intrusion detection and response.
Vulnerability assessment and management.
Authentication and access control.
Security analytics.
Threat intelligence and information sharing.
Privacy protection.
Cybersecurity risk assessment.
Secure network communication.

Published Papers

  • Open Access


    A Deepfake Detection Algorithm Based on Fourier Transform of Biological Signal

    Yin Ni, Wu Zeng, Peng Xia, Guang Stanley Yang, Ruochen Tan
    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5295-5312, 2024, DOI:10.32604/cmc.2024.049911
    (This article belongs to the Special Issue: Applications of Artificial Intelligence for Information Security)
    Abstract Deepfake-generated fake faces, commonly utilized in identity-related activities such as political propaganda, celebrity impersonations, evidence forgery, and familiar fraud, pose new societal threats. Although current deepfake generators strive for high realism in visual effects, they do not replicate biometric signals indicative of cardiac activity. Addressing this gap, many researchers have developed detection methods focusing on biometric characteristics. These methods utilize classification networks to analyze both temporal and spectral domain features of the remote photoplethysmography (rPPG) signal, resulting in high detection accuracy. However, in the spectral analysis, existing approaches often only consider the power spectral density… More >

Share Link