Scope
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In recent years, the increasing sophistication of cyber threats has necessitated the development of advanced techniques for cybersecurity analysis and defense. Intelligent computing-based time series analysis has emerged as a powerful tool for identifying patterns, anomalies, and trends in security-related data, enabling proactive threat detection and response. In the realm of cybersecurity, the use of intelligent computing-based time series analysis has gained significant traction due to its ability to enhance threat detection, anomaly identification, and incident response. By leveraging machine learning, deep learning, and other intelligent computing techniques on time-stamped data, organizations can proactively defend against evolving cyber threats and mitigate risks effectively. This special issue aims to bring together cutting-edge research and insights on the application of intelligent computing-based time series analysis in cybersecurity. By fostering collaboration and knowledge exchange in this rapidly evolving field, we seek to advance the state-of-the-art in cybersecurity analytics and contribute to the development of more robust defense mechanisms against cyber threats.


Topics of Interest
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This special issue solicits original research articles, experimental and review articles, and database/software articles. Topics of interest include, but are not limited to:

Machine learning and deep learning approaches for time series analysis in cybersecurity
Anomaly detection and threat prediction using time series data
Incident response and forensic analysis through time series techniques
Behavioral analysis and user profiling for cybersecurity
Real-time monitoring and alerting systems based on time series data
Integration of threat intelligence with time series analysis
Case studies, applications, and practical implementations of intelligent computing in cybersecurity
Privacy-Preserving Techniques for Time Series Analysis in Cybersecurity
Explainable AI for Interpretable Time Series Analysis in Cybersecurity
Blockchain Technology for Secure Time Series Analysis in Cybersecurity
Scalable Distributed Computing for Real-Time Time Series Analysis
Human-Centric Design of Intelligent Computing Systems in Cybersecurity


Guest Editors
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Le Sun, Nanjing University of Information Science and Technology, China
Deepak Gupta, Maharaja Agrasen Institute of Technology, India
Yudong Zhang, University of Leicester, UK



Submission Instructions
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Please indicate in your cover letter that your submission is intended for inclusion in the special issue.

Submission Deadline: June 3, 2025