The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A framework for detection and measurement of phishing attacks
Abstract
Phishing is form of identity theft that combines social engineering techniques and sophisticated attack vectors to harvest financial information from unsuspecting consumers. Often a phisher tries to lure her victim into clicking a URL pointing to a rogue page. In this paper, we focus on studying the structure of URLs employed in various phishing attacks. We find that it is often possible to tell whether or not a URL belongs to a phishing attack without requiring any knowledge of the corresponding page data. We describe several features that can be used to distinguish a phishing URL from a benign one. These features are used to model a logistic regression filter that is efficient and has a high accuracy. We use this filter to perform thorough measurements on several million URLs and quantify the prevalence of phishing on the Internet today.
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(1990) · Choice Reviews Online · doi:10.5860/choice.27-3338 · Cited by 35,305
Cited by
Beyond blacklists: learning to detect malicious web sites from suspicious URLs
Ma, J., Saul, L. K., Savage, S., & Voelker, G. M. (2009) · Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1557019.1557153 · Cited by 803
Chiew, K. L., Tan, C. L., Wong, K., Yong, K. S. C., & Tiong, W. K. (2019) · Information Sciences · doi:10.1016/j.ins.2019.01.064 · Cited by 348
PhishStorm: Detecting Phishing With Streaming Analytics
Marchal, S., Francois, J., State, R., & Engel, T. (2014) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2014.2377295 · Cited by 271
A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks
Heartfield, R., & Loukas, G. (2016) · ACM Computing Surveys · doi:10.1145/2835375 · Cited by 202
A survey of phishing attack techniques, defence mechanisms and open research challenges
Jain, A. K., & Gupta, B. B. (2022) · Enterprise Information Systems · doi:10.1080/17517575.2021.1896786 · Cited by 192
Metadata
- Authors
- Garera, S., Provos, N., Chew, M., & Rubin, A. D.
- Venue
- Proceedings of the 2007 ACM workshop on Recurring malcode
- Publisher
- ACM
- Published
- 2007-11-02
- Pages
- 1-8
- OpenAlex
- W2053774863
- Cited by
- 489
- References
- 1
- FWCI
- 8.24
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Garera, S., Provos, N., Chew, M., & Rubin, A. D. (2007). A framework for detection and measurement of phishing attacks. Proceedings of the 2007 ACM workshop on Recurring malcode. https://doi.org/10.1145/1314389.1314391
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