2026-10-10T21:00:58Zhttps://iris.cnr.it/oai/request

oai:iris.cnr.it:20.500.14243/1045352024-05-01T01:19:44Zcom_20.500.14243_46com_20.500.14243_21col_20.500.14243_47ou_ou198

Worm detection using e-mail data mining M Aiello D A Avanzini D Chiarella G Papaleo Aiello, M A Avanzini, D Chiarella, D Papaleo, G Data Mining E-mail Early Detection Worm 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 info:eu-repo/semantics/conferenceObject https://hdl.handle.net/20.500.14243/104535 eng PRISE