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Computer Science - Theoretical Computer Science | Applications of Data Mining in Computer Security

Applications of Data Mining in Computer Security

Barbará, Daniel, Jajodia, Sushil (Eds.)

2002, XX, 252 p.

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Data mining is becoming a pervasive technology in activities as diverse as using historical data to predict the success of a marketing campaign, looking for patterns in financial transactions to discover illegal activities or analyzing genome sequences. From this perspective, it was just a matter of time for the discipline to reach the important area of computer security. Applications Of Data Mining In Computer Security presents a collection of research efforts on the use of data mining in computer security.

Applications Of Data Mining In Computer Security concentrates heavily on the use of data mining in the area of intrusion detection. The reason for this is twofold. First, the volume of data dealing with both network and host activity is so large that it makes it an ideal candidate for using data mining techniques. Second, intrusion detection is an extremely critical activity. This book also addresses the application of data mining to computer forensics. This is a crucial area that seeks to address the needs of law enforcement in analyzing the digital evidence.

Content Level » Research

Keywords » Information - Variable - architecture - data mining - genome - knowledge - security

Related subjects » Artificial Intelligence - Communication Networks - Security and Cryptology - Software Engineering - Theoretical Computer Science

Table of contents 

List of Figures. List of Tables. Preface. 1. Modern Intrusion Detection, Data Mining, and Degrees of Attack Guilt; S. Noel, et al. 2. Data Mining for Intrusion Detection; K. Julisch. 3. An Architecture for Anomaly Detection; D. Barbará, et al. 4. A Geometric Framework for Unsupervised Anomaly Detection; E. Eskin, et al. 5. Fusing a Heterogeneous Alert Stream into Scenarios; O. Dain, K. Cunningham. 6. Using MIB II Variables for Network Intrusion Detection; Xinzhou Qin, et al. 7. Adaptive Model Generation; A. Honig, et al. 8. Proactive Intrusion Detection; J.B.D. Cabrera, et al. 9. References. Index.

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