USE OF EXPERT SYSTEMS TO PREDICT ATTACKS ON WEB-BASED SERVERS - Ariffin, M. Zainal; Fauzul Hakim, Hildhan (Universitas Ngeri Malang, 2024)
Cyber-attacks are on the rise, and various types of threats can compromise data confidentiality, integrity, and availability. Reports from the National Cyber and Crypto Agency (BSSN) and research by Check Point indicate a significant increase in cyber-attacks. These attacks often occur due to a lack of understanding and security testing of systems. In this context, the fundamental rules of the CIA (Confidentiality, Integrity, and Availability) become a crucial foundation for system security. Self-testing through penetration testing methods emerges as a solution to identify security vulnerabilities. Therefore, this research aims to develop an expert system using the OWASP Zap penetration testing tool to predict attacks on web-based servers. Utilizing a rule-based algorithm, the output of this expert system will provide results containing the type of attack, CIA classification, score, solutions, and more. In this study, testing and evaluation of the expert system are conducted on domains within the State University of Malang as the target. The test results indicate a satisfactory expert system performance with an accuracy rate of 91.62 percent. This evaluation is expected to provide a comprehensive insight into the expert system's performance in securing the system, enabling developers or campus administrators to address any issues promptly..