In today’s world, connected systems, social networks, and mobile communications create a massive flow of data, which is prone to cyberattacks. This needs fast and accurate detection of cyber-attacks. Intelligent systems and Data analytics are important components when issues pertaining to effective security solutions become the subject of discussion. This is because there is an impending need for high volume and high velocity data from different sources to detect anomalies as soon as they are discovered. This will help reduce significantly the vulnerability of the systems as well as improve their resilience to cyber Attacks. The capability to process large volumes of information at real time through utilization of tools for data analytics has many advantages vital for analysis of cybersecurity systems. Moreover, the data collected from sophisticated intelligent systems, cloud systems, networks, sensors, computers, intrusion detection systems could be used to identify vital information. This information could be used to detect how vulnerable the systems are to risk factors, and so effective cyber security solutions can be developed. In addition to that, the utilization of data analytics tools in the cybersecurity field gives new insights through considering factors such as zero-day attack detection, real time analysis, resource constrained data processing among others.

The AISC 2025 symposium addresses the use of advanced intelligent systems in providing cybersecurity solutions in many fields, and the challenges, approaches, and future directions. We invite the submission of original papers on all topics related to Intelligent Systems for Cybersecurity, with special interest in but not limited to:

Intelligent systems for effective detection of cyber-attacks
Advanced Intelligent systems and data analytics for Cloud/Edge systems security
Malware detection using intelligent systems Vulnerability assessment
Intelligent systems for intrusion detection in Internet of Things (IoT) systems
Network forensics using intelligent systems and data analytics
Data Analytics for privacy-by-design in smart health
Datasets, benchmarks, and open-source packages
Recourse efficient deep learning
Adversarial Machine learning and Backdoor Attacks
Blockchain Systems for Cyber Security
Trustworthy AI Systems
Intelligent Systems for Misinformation Detection