Mauro Allegretta
Community Detection Algorithms for Darknet Traffic Analysis.
Rel. Marco Mellia, Idilio Drago. Politecnico di Torino, Corso di laurea magistrale in Communications And Computer Networks Engineering (Ingegneria Telematica E Delle Comunicazioni), 2019
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Abstract
Community Detection Algorithms for Darknet Traffic Analysis Today the diffusion of internet is widespread and so the defence from cyber-attacks is very relevant. Among the possible attacks there are large-scale network probing activities and DDoS (Distributed Denial of Service). One way to defend ourselves is to detect and predict via passive monitoring, keeping track of the traces of attacks that are collected by the Darknets: backscattering packets and port scans. Darknets are range of advertised, but unused, IP addresses, studying the darknet traffic at our disposal we try to propose a simple way to cluster, visualize and analyse the spurious data.
In this thesis we focus on a complex network approach to the problem: instead of representing the packet records in a highly dimensional euclidean space of points we create a relationship traffic graph on the model of a social network, formed by nodes, e.g
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