Open Access
| Issue |
ITM Web Conf.
Volume 32, 2020
International Conference on Automation, Computing and Communication 2020 (ICACC-2020)
|
|
|---|---|---|
| Article Number | 03004 | |
| Number of page(s) | 6 | |
| Section | Computing | |
| DOI | https://doi.org/10.1051/itmconf/20203203004 | |
| Published online | 29 July 2020 | |
- Jhen-Hao Li, Sheng-De Wang. PhishBox: An Approach for Phishing Validation and Detection. 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSci Tec) [Google Scholar]
- Samuel Marchal, Jérôme François, Radu State, Thomas Engel. ] PhishStorm: Detecting Phishing With Streaming Analytics. Engel IEEE Transactions on Network and Service Management Year: 2014, volume: 11 [Google Scholar]
- P.A. Barraclough, G. Sexton & N. Aslam. Online Phishing Detection Toolbar for Transactions. Science and Information Conference 2015 July 28-30 2015 | London, UK Computer Science and Digital Technology University of Northumbria Newcastle Upon Tyne, NE 18ST, United Kingdom. [Google Scholar]
- Samuel Marchal; Giovanni Armano; Tommi Gröndahl; Kalle Saari; Nidhi Singh; N. Asokan. Off-the-Hook: An Efficient and Usable Client-Side Phishing Prevention Application. IEEE Transactions on ComputersYear: 2017, volume: 66. [Google Scholar]
- Ludl, C., McAllister, S., Kirda, E., & Kruegel, C. (2007). On the effectiveness of techniques to detect phishing sites.In Detection of Intrusions and Malware, and Vulnerability Assessment (pp. 20-39). Springer Berlin Heidelberg. [CrossRef] [Google Scholar]
- Y. Pan, X. Ding, “Anomaly based web phishing page detection”, Proc. 22nd Annu. Comput. Security Appl. Conf., pp. 381-392, 2006. [Google Scholar]
- M. Zabihimayvan and D. Doran, “Fuzzy Rough Set Feature Selection to Enhance Phishing Attack Detection,” 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), New Orleans, LA, USA, 2019, pp. 1-6 [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.