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Detecting Input Validation Attacks of Web Apps and Developing Metrics for Their Ranks


Mehrnoush Vaseghipanah, Nasser Modiri and Sam Jabbehdari


Vol. 17  No. 6  pp. 191-195


Input validation attacks against web applications are very common. These attacks lead to web application damage, information leakage, unauthorized access, etc. Therefore it is very important to have some effective metrics to provide a much better detection, and to rank these metrics to measure how successful they are. In this paper we developed three metrics for detection of input validation (IV) attacks and allocated a rank to each. Also a method is presented here for detection of input validation in web apps with zero false positive rate.


Input Validation Attacks, IV Attacks Detection, Detection Metrics, Web Apps Attack Detection.