The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Cantina: a content-based approach to detecting phishing web sites
Abstract
Phishing is a significant problem involving fraudulent email and web sites that trick unsuspecting users into revealing private information. In this paper, we present the design, implementation, and evaluation of CANTINA, a novel, content-based approach to detecting phishing web sites, based on the TF-IDF information retrieval algorithm. We also discuss the design and evaluation of several heuristics we developed to reduce false positives. Our experiments show that CANTINA is good at detecting phishing sites, correctly labeling approximately 95% of phishing sites.
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Citations
Cites
Decision strategies and susceptibility to phishing
Downs, J. S., Holbrook, M. B., & Cranor, L. F. (2006) · Proceedings of the second symposium on Usable privacy and security - SOUPS '06 · doi:10.1145/1143120.1143131 · Cited by 352
Self-citation
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
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 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
(2012) · doi:10.1109/ecrime.2012.6489521 · Cited by 148
Look before you leap: Detecting phishing web pages by exploiting raw URL and HTML characteristics
Opara, C., Chen, Y., & Wei, B. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.121183 · Cited by 129
Metadata
- Authors
- Zhang, Y., Hong, J. I., & Cranor, L. F.
- Venue
- Proceedings of the 16th international conference on World Wide Web
- Publisher
- ACM
- Published
- 2007-05-08
- Pages
- 639-648
- OpenAlex
- W2139565456
- Cited by
- 757
- References
- 1
- FWCI
- 17.21
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Zhang, Y., Hong, J. I., & Cranor, L. F. (2007). Cantina: a content-based approach to detecting phishing web sites. Proceedings of the 16th international conference on World Wide Web. https://doi.org/10.1145/1242572.1242659
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
