Texas A&M’s main campus in College Station, located in the core of the Houston-Dallas-Austin triangle and within a two-hour drive of 26 million of the state’s 28 million population, is home to more than 69,000 students. Another 5,200 are at the Galveston and Qatar branch campuses, as well as the School of Law, Higher Education Center in McAllen, and Health Science Center sites around Texas.
Second International Symposium on Advanced Intelligent Systems for Cybersecurity (AISC2022)
Billions of linked systems have produced an endless flow of data that is vulnerable to assaults and necessitates rapid and precise cyber-attack detection. When it comes to successful security solutions, intelligent systems and data analytics are critical components. This is due to an upcoming requirement for large volume, high-velocity data from many sources in order to spot abnormalities as soon as they occur. This will drastically lower the systems’ susceptibility while also increasing their resilience.
The capacity to analyze massive amounts of data in real-time using data analytics tools provides a number of advantages that are critical for cybersecurity system research. Furthermore, data from sophisticated intelligent systems, cloud systems, networks, sensors, computers, and intrusion detection systems might be leveraged to locate critical information. This information might be utilized to determine how vulnerable the systems are to risk factors, allowing for the development of an effective cyber security solution. Furthermore, the use of data analytics tools in the cybersecurity industry provides fresh insights by taking into account elements like zero-day attack detection, real-time analysis, and resource-restricted data processing, among others.
The AISC 2022 symposium will focus on the problems, techniques, and future directions of advanced intelligent systems in offering cybersecurity solutions in a variety of industries. Original papers on any issue connected to Intelligent Systems for Cybersecurity are welcome, with a particular 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