Journal of Beijing University of Posts and Telecommunications

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JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM

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An Abnormal Intrusion Detection Model Based on
User's Keystrokes

    

  1. 1. Software Engineering School, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2. Information Engineering School, Beijing University of Posts and Telecommunications, Beijing 100876, China
     
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Abstract: The Apriori association rules are improved. Through mining the rules of normal user's keystrokes, we set up the user 's characteristic profiles. Then we use the profiles to do abnormal intrusion detection for a new user's key stroke data. The results show that this model can realize some functions of intrusion detection.

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