- Title
- Normandy: A Framework for Implementing High Speed Lexical Classification of Malicious URLs
- Creator
- Egan, Shaun P, Irwin, Barry V W
- 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, pdf
- Language
- English
- Relation
- Proceedings of Southern African Telecommunication Networks and Applications Conference (SATNAC), 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), 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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Collections
Irwin, Barry V W (Prof)
RU Department of Computer Science
SDG 09. Industry, Innovation and Infrastructure
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details | SOURCE1 | Normandy.pdf | 355 KB | Adobe Acrobat PDF | View Details |