Name
Abstract | ||
|---|---|---|
Context: In the fight against phishing attacks, phishing prediction heuristics are important in developing solutions. However, phishing attacks continue to grow today, reflecting on the need for higher precision solutions. Objective: This article focuses on phishing prediction based on a set of features. The purpose of this proposal is to evaluate the static features used and observe their occurrence in the current phishing. Static aspects refer to elements such as keywords and patterns over the phishing URL. Method: The study methodology makes use of a survey with a set of 12 features, raised both in this study and from third-party studies, submitted to three distinct samples of phishing and legitimate sites during the year 2018. Results: Although research on phishing prediction has developed considerably, it is possible to note that certain features are of low relevant and others have not accompanied the changes in the scenario and may need to be discarded. Some features are found more regularly in phishing and could be more efficiently exploited, indicating that further investigations need to be carried out. Conclusion: In addition to the quantitative data, the study also performed a qualitative analysis of behaviors, managing to identify aspects such as relevance, relationships, and similarities among the features. It is expected that these results obtained can help in developing new heuristic approaches or improve the robustness of the existing ones. (C) 2019 Elsevier Ltd. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.cose.2019.101613 | Computers & Security |
Keywords | Field | DocType |
Phishing,Social Engineering attacks,Cybercrimes,Frauds,Heuristic prediction | Heuristic,Phishing,Computer security,Computer science,Robustness (computer science),Heuristics,Artificial intelligence,Machine learning | Journal |
Volume | ISSN | Citations |
88 | 0167-4048 | 2 |
PageRank | References | Authors |
0.39 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carlo Marcelo Revoredo da Silva | 1 | 12 | 3.35 |
| Eduardo Luzeiro Feitosa | 2 | 2 | 0.39 |
| Vinicius C. Garcia | 3 | 53 | 4.57 |