International Journal of Scientific Engineering and Technology
  • Year: 2013
  • Volume: 2
  • Issue: 12

Review of Anomaly Detection based on Classifying Frequent Traffic Patterns

  • Author:
  • Mayank Nagar, Sandeep Kumar, Udaypal Reddy
  • Total Page Count: 5
  • Page Number: 1173 to 1177

CSE, RGPV, IES College Of Technology, Bhopal (M.P.), India

*Author: nagar.mayank22@gmail.com.

**Co guide: sandeep.kumar@outlook.in

Online published on 4 November, 2017.

Abstract

As internet grow rapidly and numerous applications use it as a larger communication media. Many organizations are Internet dependent for their working methodology. This will lead a larger amount of network traffic. Network traffic anomaly is kind of status that the traffic activities deviated from its normal condition behaviors. The characteristic of network traffic anomaly is that it explodes unexpectedly without any warning. It will lead immense damage to networks and network apparatus in a minimum time. Detection of network traffic anomalies is vital for network operators as it facilitates to classify security incidents and to observe the availability of network related services. In this paper we are going to present various methods or schemes for anomaly detection. In this paper we also focus on various schemes that are applicable to enhance the network performance.