Second International Symposium on Advanced Intelligent Systems for Cybersecurity (AISC2022)
5 septembre 2022
00:00
United States | Texas, San Antonio
n today’s world, billions of connected systems created an ever ending flow of data, which is prone to cyberattacks, which needs a fast and accurate detection of cyber-attacks. Intelligent systems and Data analytics are important components when matters 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 arise. This will help reduce significantly the vulnerability of the systems as well as improve their resilience. The capability to process large volumes of information real time through utilization of tools for data analytics has many advantages vital for analysis of cybersecurity systems. Moreover, the data collected from advanced 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 an effective Cyber security solution 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 2022 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
Resource efficient deep learning
Adversarial Machine learning and Backdoor Attacks
Blockchain Applications for Cyber Security