ANALISA KOMBINASI NAIVE BAYES DAN MHR (MEAN OF HORNER'S RULE) PADA KLASIFIKASI KEYSTROKE DYNAMIC AYTHENTICATION
Rahayu Nurul Khasanah · UMM Institutional Repository (University of Maine at Machias) · 2021
Keystroke Dynamics Authentication (KDA) is a method which used to identify someone based on a typing pattern or typing rhythm in a system. Everyone’s typing behaviour is considered unique. Thus, this uniqueness of typing rhythm can be used as a foundation for password security. The development of technology is followed by humans’ need for security regarding to data and privacy since hacker’s skill of data theft has become more advanced. One of many ways to secure private data is by using password. Therefore, for a better security, ways such as finger print scan, retina scan, et cetera are highly recommended. On the other hand, previous methods are considered expensive. The main advantage of KDA is user would not know that the system is utilizing KDA. Thus, the researcher tries to suggest the combination of Naïve Bayes and MHR (Mean of Horner’s Rule) to classify someone whether he or she an attacker or non-attacker. This research shows that the accuracy level of FAR and FRR are getting better than the previous research.