Stefano Giannuzzi
Artificial Intelligence for Security Attacks Detection.
Rel. Antonio Lioy, Diana Gratiela Berbecaru, Daniele Canavese. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2022
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Abstract
In recent years, there has been an explosion in cybersecurity attacks. As countermeasures are implemented, new variants of attacks appear in the meantime. Historically, Intrusion Detection Systems (IDS) have been typically employed to detect cyberattacks or anomalous behaviour in networks. Nowadays, two types of IDS exist: signature-based and anomaly-based. The first type of IDS is typically effective only against attacks that have been discovered and for which a signature exists, which is saved in dedicated databases across the globe. The second type of IDS is highly required nowadays because it can detect attacks without registered signatures using Machine Learning and Deep Learning techniques.
Such IDS perform traffic analysis, exploiting data of different levels and alerts if a suspicious pattern is encountered
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