Enhancing Computer Security and Smart Technology introduces the problems of computer security to researchers with a machine learning background, then introduces machine learning concepts to computer security professionals.

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

Contents

Cyber-Security and Cyber-Trust

• Cyber-Security
• Cyber-Trust
• What the Future Holds

Network Firewalls

• 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

Web Application Security: The Next Battleground

• Threats to Web Applications
• Vulnerabilities in Web Applications
• Attack Techniques
• Preventing Vulnerabilities in Web Applications

Relevance of Machine Learning

• 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

Machine Learning in Intrusion Detection

• Intrusion Detection
• Machine Learning Approaches to Anomaly Detection
• Audit Data.
• Issues in Anomaly Detection
• Open Questions and Future Directions
• Illustrative Example: Adaptive Anomaly Detection

Cyber-Security Challenges: Designing Efficient

• Intrusion Detection Systems and Anti-Virus Tools
• 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

Artificial Immune Systems in Intrusion Detection

• Artificial Immune Systems
• RNS
• Intrusion Detection Problem
• Experimentation

Application of Wavelets in Network Security

• 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

Application of Exploratory Multivariate Analysis for Network Security

• Abstract
• The Intrusion Detection Problem
• The S Language and Its Environment
• Introduction to Multivariate Analysis Methods
• DoS and Network Probe Attacks
• Data Collection and Preprocessing

Index

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