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MET: An Experimental System for Malicious Email Tracking

Manasi Bhattacharyya; Shlomo Hershkop; Eleazar Eskin

Title:
MET: An Experimental System for Malicious Email Tracking
Author(s):
Bhattacharyya, Manasi
Hershkop, Shlomo
Eskin, Eleazar
Date:
Type:
Articles
Department:
Computer Science
Permanent URL:
Notes:
New Security Paradigms Workshop: proceedings, September 23 -26, 2002, Virginia Beach, VA (New York: Association for Computing Machinery, 2002), pp. 3-10.
Abstract:
Despite the use of state of the art methods to protect against malicious programs, they continue to threaten and damage computer systems around the world. In this paper we present MET, the Malicious Email Tracking system, designed to automatically report statistics on the flow behavior of malicious software delivered via email attachments both at a local and global level. MET can help reduce the spread of malicious software worldwide, especially self-replicating viruses, as well as provide further insight toward minimizing damage caused by malicious programs in the future. In addition, the system can help system administrators detect all of the points of entry of a malicious email into a network. The core of MET's operation is a database of statistics about the trajectory of email attachments in and out of a network system, and the culling together of these statistics across networks to present a global view of the spread of the malicious software. From a statistical perspective sampling only a small amount of traffic (for example, .1 %) of a very large email stream is sufficient to detect suspicious or otherwise new email viruses that may be undetected by standard signature-based scanners. Therefore, relatively few MET installations would be necessary to gather sufficient data in order to provide broad protection services. Small scale simulations are presented to demonstrate MET in operation and suggests how detection of new virus propagations via flow statistics can be automated.
Subject(s):
Computer science
Publisher DOI:
10.1145/844102.844104
Item views:
203
Metadata:
text | xml

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