Enhancing Computer Security with Smart Technology

Published:
November 21, 2005 by Auerbach Publications - 288 Pages
Author(s):
V. Rao Vemuri, University of California, Livermore, USA

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Hardback
$139.95
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ISBN 9780849330452
Cat# AU3045
 

Features

  • Describes machine learning methods and tools and their application to cyber security
  • Explores computer attack taxonomy and provides examples of attack signatures
  • Presents feature selection, extraction, and ranking algorithms
  • Discusses limitations of current anti-virus tools in detecting malware variants
  • Applies the immune system metaphor to computer security problems
  • Examines the potential of wavelets in detecting the early stages of attacks
  • Proposes the use of a statistical toolbox and environment to streamline the computational steps of security applications

    • Summary

    Divided into two major parts, Enhancing Computer Security with Smart Technology introduces the problems of computer security to researchers with a machine learning background, then introduces machine learning concepts to computer security professionals.

    Realizing the massive scope of these subjects, the author concentrates on problems related to the detection of intrusions through the application of machine learning methods and on the practical algorithmic aspects of machine learning and its role in security.

    A collection of tutorials that draw from a broad spectrum of viewpoints and experience, this volume is made up of chapters written by specialists in each subject field. It is accessible to any professional with a basic background in computer science. Following an introduction to the issue of cyber-security and cyber-trust, the book offers a broad survey of the state-of-the-art in firewall technology and of the importance of Web application security. The remainder of the book focuses on the use of machine learning methods and tools and their performance.

    Table of Contents

    Cyber-Security and Cyber-Trust
    V Rao Vemuri
    Introduction
    Cyber-Security
    Cyber-Trust
    What the Future Holds

    Network Firewalls
    Kenneth Ingham and Stephanie Forrest
    Abstract
    Introduction
    The Need for Firewalls
    Firewall Architectures
    Firewalls at Various ISO Network Layers
    Other Approaches
    Firewall Testing
    What Firewalls Do Not Protect Against
    Future Challenges for Firewalls
    Conclusion
    References

    Web Application Security: The Next Battleground
    Abhishek Kumar, Roshen Chandran, and Vinod Vasudevan
    Threats to Web Applications
    Vulnerabilities in Web Applications
    Attack Techniques
    Preventing Vulnerabilities in Web Applications
    Conclusion
    Notes
    References

    Relevance of Machine Learning
    V Rao Vemuri
    Introduction
    Place of Intrusion Detection in the Security Landscape
    Machine Learning beyond Intrusion Detection
    Machine Learning and Computational Learning Theory
    Some Popular Machine Learning Methods
    Making Machine Learning More Useful
    Summary
    References

    Machine Learning in Intrusion Detection
    Yihua Liao and V Rao Vemuri
    Introduction
    Intrusion Detection
    Machine Learning Approaches to Anomaly Detection
    Audit Data.
    Issues in Anomaly Detection
    Open Questions and Future Directions
    Illustrative Example: Adaptive Anomaly Detection
    Summary
    References

    Cyber-Security Challenges: Designing Efficient
    Intrusion Detection Systems and Anti-Virus Tools
    Srinivas Mukkamala, Andrew Sung, and Ajith Abraham
    Introduction to IDSs
    A Review on IDSs
    Computer Attack Taxonomy
    Significant Feature Selection for Intrusion Detection
    Detection of Probes and DoS Attacks
    Attacks on IDSs
    Attacks on Anti-Virus Tools
    Conclusions
    Acknowledgments
    References

    Artificial Immune Systems in Intrusion Detection
    Dipankar Dasgupta and Fabio Gonzalez
    Introduction
    Artificial Immune Systems
    RNS
    Intrusion Detection Problem
    Experimentation
    Summary
    Bibliography

    Application of Wavelets in Network Security
    Challa S. Sastry and Sanjay Rawat
    Introduction
    A Brief Introduction to Self-Similarity
    A Brief Introduction to Wavelet Analysis
    Application of Wavelets
    Wavelets for HIDS
    Wavelets for Network-Based IDS
    Simulation Results
    An Observation for Future Work and Conclusion
    Appendix
    Acknowledgment
    References

    Application of Exploratory Multivariate Analysis
    for Network Security
    Khaled Labib and V Rao Vemuri
    Abstract
    Introduction
    The Intrusion Detection Problem
    The S Language and Its Environment
    Introduction to Multivariate Analysis Methods
    DoS and Network Probe Attacks
    Data Collection and Preprocessing
    Results
    Acknowledgment
    References
    Index

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