Normandy: A Framework for Implementing High Speed Lexical Classification of Malicious URLs

Egan, Shaun P; Irwin, Barry V W

Title: Normandy: A Framework for Implementing High Speed Lexical Classification of Malicious URLs
Creator: Egan, Shaun P
Creator: Irwin, Barry V W
Date Issued: 2012
Date: 2012
Type: text
Type: article
Identifier: http://hdl.handle.net/10962/427958
Identifier: vital:72476
Identifier: https://www.researchgate.net/profile/Barry-Ir-win/publication/326224974_Normandy_A_Framework_for_Implementing_High_Speed_Lexical_Classification_of_Malicious_URLs/links/5b3f21074585150d2309dd50/Normandy-A-Framework-for-Implementing-High-Speed-Lexical-Classification-of-Malicious-URLs.pdf
Description: Research has shown that it is possible to classify malicious URLs using state of the art techniques to train Artificial Neural Networks (ANN) using only lexical features of a URL. This has the advantage of being high speed and does not add any overhead to classifications as it does not require look-ups from external services. This paper discusses our method for implementing and testing a framework which automates the generation of these neural networks as well as testing involved in trying to optimize the performance of these ANNs.
Format: 2 pages
Format: pdf
Language: English
Relation: Proceedings of Southern African Telecommunication Networks and Applications Conference (SATNAC)
Relation: Egan, S.P. and Irwin, B., Normandy: A Framework for Implementing High Speed Lexical Classification of Malicious URLs. Southern Africa Telecommunication Networks and Applications Conference (SATNAC)
Relation: Proceedings of Southern African Telecommunication Networks and Applications Conference (SATNAC) volume 2012 number 1 1 2 2012 Conference
Rights: Publisher
Rights: Use of this resource is governed by the terms and conditions of the Southern Africa Telecommunication Networks and Applications Conference (SA TNAC) Statement (https://www.satnac.org.za/)

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Irwin, Barry V W (Prof)

RU Department of Computer Science

SDG 09. Industry, Innovation and Infrastructure

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