ARTIFICIAL NEURAL NETWORK FOR MISUSE DETECTION

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INTRODUCTION


INTRUSION DETECTION SYSTEMS (IDS)

• Host-based IDS
• Network-based IDS
• Vulnerability-assessment IDS


COMPONENT OF Of IDS

• An information source that provides a stream of event records
• An analysis engine that identifies signs of intrusions
• A response component that gene rates reactions based
on the outcome of the analysis engine.


Neural Network Intrusion Detection Systems

• Computer attack
• Typical characteristics of User
• Computer Viruses
• Malicious Software in Computer Network


NEURAL ENGINE
• Based Anomaly intrusion detection
• Establish profiles of normal user and compare user behaviors to those profiles
• Investigation of total behaviors of the user


Disadvantages
• A statistical assumption is required



Neural Network as Stand alone System

• Data is received from Network Stream and analyzed for misuse
• Indicative of data is forwarded to automated intrusion response system


CONCLUSION

The early results of tests of these technologies show significant promise, and our future work will involve the refinement of the approach and the development of a full-scale demonstration system