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Customizable Method of Automatically Detecting Malicious User Activity in Web Applications (thesis)
| Content Provider | Semantic Scholar |
|---|---|
| Author | Jang, Han Gil |
| Copyright Year | 2015 |
| Abstract | With the increase in the use of the web and security threats on web applications also at its highest point, the need for better security measures also increases. In this thesis we present a customizable method of automatically detecting malicious user activity for web applications. The customizable method has four phases. First, the method is uses information gathered from the web application access logs to represent the data in a certain way to create individual and typical user profiles. Then with the profile it goes through the training phase to compare the different profiles to create a threshold. Then threshold is then used to decide whether or not a new user is a malicious user or not. Finally, with new incoming information and the testing results, the system is calibrated to provide improved results in the future. In this thesis the design, implementation and results from a prototype following the method is presented as well as recommendations for security admins to follow in implementing this method into current web applications. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://repository.wlu.edu/bitstream/handle/11021/32153/RG38_Jang_CSCI_2015.pdf?isAllowed=y&sequence=1 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
