Improved Intrusion Detection System Using Discriminative learning Approach (A Review)
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 3
Abstract
Abstract: With the advent of anomaly-based intrusion detection systems, many approaches and techniques have been developed to track novel attacks on the systems. High detection rate of 98% at alow alarm rate of 1% can be achieved by using these techniques. Though anomaly-based approaches are efficient, signature-based detection is preferred for mainstream implementation of intrusion detection systems. As a variety of anomaly detection techniques were suggested, it is difficult tocompare the strengths, weaknesses of these methods. The reason why industries don‟t favor the anomaly-based intrusion detection methods can be well understood by validating the efficiencies of the all the methods. To investigate this issue, the current state of the experiment practice in the field of anomaly-based intrusion detection is reviewed and survey recent studies in this. This paper contains summarization study and identification of the drawbacks of formerly surveyed works..
Authors and Affiliations
Charanjeet Kaur, , Dr. Vinay Gautam(Asst Professor)
Keywords
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- EP ID EP94352
- DOI 10.9790/0661-16397379
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