We propose a new technique to detect internet worm. We base our research on the fact that an indirect worm (a worm spreading by e-mail) needs to spread quickly and so it sends a lot of e-mail in a short while, producing an anomalous behaviour. Moreover we found stealthy worms through detecting traffic anomalies. We worked on a mail-server log of a real network and the results obtained drove us to detect indirect worm with different approaches based on various parameters (global email flow, single host e-mail flow, reject, sender field analysis).

Worm detection using e-mail data mining

M Aiello;D Chiarella;G Papaleo
2006

Abstract

We propose a new technique to detect internet worm. We base our research on the fact that an indirect worm (a worm spreading by e-mail) needs to spread quickly and so it sends a lot of e-mail in a short while, producing an anomalous behaviour. Moreover we found stealthy worms through detecting traffic anomalies. We worked on a mail-server log of a real network and the results obtained drove us to detect indirect worm with different approaches based on various parameters (global email flow, single host e-mail flow, reject, sender field analysis).
2006
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
Data Mining
E-mail
Early Detection
Worm
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/104535
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