Using SVM Technique to Detect Unauthorized Use Under Windows Operating Systems

• Main Authors: Chun-Hao Lai, 賴俊豪
• Other Authors: 陳奕明
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/51867213261125340934

碩士 === 國立中央大學 === 資訊管理研究所 === 95 === Security damage about “Unauthorized use” are usually be discovered after it happened. And it costs about 50% financial loss in 30% respondents in 2006, CSI/FBI. Because of the popularity of Microsoft Window operation system, we discuss the “anomaly user behavior” in recent papers. After that we propose a view about “too large”, “include too many system information” in dataset that used for building normal user behavior model. It brings information security analyzer a lot of inconvenient in Microsoft Window OS environment.Then, we reference the thought, “Window Title”, and recommend a kind of dataset. The proposed dataset takes advantage of “few dataset”, “distinguish anomaly user behavior”.Finally, we use “Support Vector Machine” to verify the effect, and give some experimental results to explain the cuts of the dataset in our proposed system.