Leaning of Anomaly Detection in Network Traffic using Fuzzy Approach |
Author(s): |
| Krunal Khurana , Anand Institute of Information Science, Anand, Gujarat, India; Prof.(Dr.) Priti S. Sajja, P.G. Department of Computer Science, SP University, |
Keywords: |
| Network Security, Network Monitoring, Anomaly Detection, Security Attacks, IDS |
Abstract |
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Anomaly detection in network traffic is essential to identify security incidents and to monitor network services. Typically the Anomaly detection used in a variety of applications such as fraud detection for online banking transaction, intrusion detection for cyber-security, fault detection in safety of critical systems, and military surveillance for enemy activities. The most existing intrusion detection systems deploy signature-based method or data mining-based method which completely rely on fix set of rules and policies for anomaly detection. In this paper we present new behavior-based anomaly detection that is capable of detecting previously unseen network attacks and threats. The main idea for this new evaluation is to reach close to the already existing approach and to provide more advantages in terms of computational complexity. |
Other Details |
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Paper ID: IJSRDV3I120644 Published in: Volume : 3, Issue : 12 Publication Date: 01/03/2016 Page(s): 940-943 |
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