- Title
- High Speed Lexical Classification of Malicious URLs
- Creator
- Egan, Shaun P, Irwin, Barry V W
- Date
- 2011
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/428055
- Identifier
- vital:72483
- Identifier
- https://www.researchgate.net/profile/Barry-Ir-win/publication/326225046_High_Speed_Lexical_Classification_of_Malicious_URLs/links/5b3f20acaca27207851c60f9/High-Speed-Lexical-Classification-of-Malicious-URLs.pdf
- Description
- It has been shown in recent research that it is possible to identify malicious URLs through lexi-cal analysis of their URL structures alone. Lightweight algorithms are defined as methods by which URLs are analyzed that do not use external sources of information such as WHOIS lookups, blacklist lookups and content analysis. These parameters include URL length, number of delimiters as well as the number of traversals through the directory structure and are used throughout much of the research in the paradigm of lightweight classification. Methods which include external sources of information are often called fully featured classifications and have been shown to be only slightly more effective than a purely lexical analysis when considering both false-positives and falsenegatives. This distinction allows these algorithms to be run client side without the introduction of additional latency, but still providing a high level of accuracy through the use of modern techniques in training classifiers. Both AROW and CW classifier update methods will be used as prototype implementations and their effectiveness will be com-pared to fully featured analysis results. These methods are selected because they are able to train on any labeled data, including instances in which their prediction is correct, allowing them to build a confidence in specific lexical features.
- Format
- 2 pages, pdf
- Language
- English
- Relation
- Proceedings of Southern African Telecommunication Networks and Applications Conference (SATNAC), Egan, S.P. and Irwin, B., 2011. High Speed Lexical Classification of Malicious URLs. Southern Africa Telecommunication Networks and Applications Conference (SA TNAC), Proceedings of Southern African Telecommunication Networks and Applications Conference (SATNAC) volume 2011 number 1 1 2 2011 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 Download | SOURCE1 | High Speed Lexical Classification of Malicious URLs.pdf | 323 KB | Adobe Acrobat PDF | View Details Download |