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A COMBINED METHOD FOR DETECTING SPAM MACHINES ON A TARGET NETWORK

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Author(s): Tala Tafazzoli | Seyed Hadi Sadjadi

Journal: International journal of Computer Networks & Communications
ISSN 0975-2293

Volume: 1;
Issue: 2;
Start page: 35;
Date: 2009;
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Keywords: spam | clustering method | K-Means clustering algorithm | HITS algorithm | anomalous behavior

ABSTRACT
The HITS and PageRank algorithms and K-Means clustering algorithm are two main methods for detecting spammachines. In PageRank algorithm, it is proposed to calculate weights based on different factors. Correctselection of weights has important role in the accuracy of the algorithm. In this paper, we propose a goodmethod for convenient selection of weights. We first executed the K-Means algorithm on the traffic of a big targetnetwork and divided IP addresses to two parties, normal and anomalous, and assigned a weight to the IPaddresses of anomalous party which is used in calculating the energy rank of the second method. With executingthe second algorithm, we found a larger set of IP addresses of spam machines and found that we have increasedthe accuracy of the algorithms perceptibly.
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