Call For Paper Volume:4 Issue:9 Sep'2017 |

DETECTING NETWORK ANOMALIES USING CUSUM and FCM

Publication Date : 30/12/2014



Author(s) :

E.M. Roopa Devi , R.C.Suganthe , B.Bhuvaneswari.


Volume/Issue :
Volume 1
,
Issue 6
(12 - 2014)



Abstract :

The network intrusion detection techniques are important to prevent our systems and networks from malicious behaviors. However, traditional network intrusion prevention such as firewalls, user authentication and data encryption have failed to completely protect networks and systems from the increasing and sophisticated attacks and malwares. Two anomaly detection techniques – CUSUM and clustering are used to find network anomalies. CUSUM detect changes based on the cumulative effect of the changes made in the random sequence instead of using a single threshold to check every variable. It involves calculating cumulative sum and determining whether a packet is normal or not. The FCM algorithm employs fuzzy partitioning such that a data point can belong to all groups with different membership grades. Together, CUSUM and FCM become a good technique in detecting network anomalies with a very less false alarm rate.


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DETECTING NETWORK ANOMALIES USING CUSUM and FCM

December 8, 2014