"May I borrow Your Filter?" Exchanging Filters to Combat Spam in a Community

Leveraging social networks in computer systems can be effective in dealing with a number of trust and security issues. Spam is one such issue where the "wisdom of crowds" can be harnessed by mining the collective knowledge of ordinary individuals. In this paper, we present a mechanism through which members of a virtual community can exchange information to combat spam. Previous attempts at collaborative spam filtering have concentrated on digest-based indexing techniques to share digests or fingerprints of emails that are known to be spam. We take a different approach and allow users to share their spam filters instead, thus dramatically reducing the amount of traffic generated in the network. The resultant diversity in the filters and cooperation in a community allows it to respond to spam in an autonomic fashion. As a test case for exchanging filters we use the popular SpamAssassin spam filtering software and show that exchanging spam filters provides an alternative method to improve spam filtering performance

The development of a social network analysis software tool

Thesis (Master)--Izmir Institute of Technology, Computer Engineering, Izmir, 2009Includes bibliographical references (leaves: 33-34)Text in English; Abstract: Turkish and Englishix, 38 leavesNowadays the amount of spam is increasing in an uncontrollable way. This situation decreases the email trust of the Internet users and reduces the usability of the emails to the critical level. On the other hand, this makes a lot of money loss for the hosting companies. There are many anti-spam tools that are developed against spammers. Some of these tools are really succesful. However; since the spammers improve their techniques, spams gain immune to these tools. In this thesis, the problem of detecting spams in in-coming and out-going emails is adressed.. To achieve this goal, an email social network is constructed by using the traffic of emails between users.While constructing this network, only information that can be gained from the email structure is used. The results on the real data set show that the techniques applied have been effective and also point to new directions of research in this area