A new Data mining Based Approach for Network Intrusion Detection.

Published on June 2016 | Categories: Documents | Downloads: 41 | Comments: 0 | Views: 269
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A new Data mining Based Approach for Network Intrusion Detection

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Abstracts
‡ In Information Security, intrusion detection is the act of detecting actions that attempt to compromise the con dentiality, integrity or availability of a resource. ‡ Intrusion detection does not, in general, include prevention of intrusions. ‡ In this paper, we are mostly focused on data mining techniques that are being used for such purposes. ‡ We debate on the advantages and disadvantages of these techniques. ‡ Finally we present a new idea on how data mining can aid IDSs.

Existing System
‡ Distributed Intrusion Detection System ‡ Emarald ‡ The MINDS system ‡ ISOA-Internet Security Officer s Assistance.

Drawbacks
‡ Cannot detect Unknown Attacks ‡ False Positive ‡ False Negative ‡ Data Overload

Proposed System
‡ ‡ ‡ ‡ ‡ ‡ Anomaly Detection Misuse or Signature based Detection. Remove the normal activity from the attacks. Identifying the false alarm signal Find the anomalies attack Identify long, ongoing patterns.

Technologies used
‡ ‡ ‡ ‡ Data summarization Data Visualization Association of the rule discovery Classification

Algorithms
‡ ‡ ‡ ‡ Binary Classification. Machine Learning Feature selection Genetic Algorithms

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