Name
Title | ||
|---|---|---|
Dynamic Trackback Strategy for Email-Born Phishing Using Maximum Dependency Algorithm (MDA). |
Abstract | ||
|---|---|---|
Generally, most strategy prefers to use fake tokens to detect phishing activity. However, using fake tokens is limited to static feature selection that needs to be pre-determined. In this paper, a tokenless trackback strategy for email-born phishing is presented, which makes the strategy dynamic. Initially, the selected features were tested on the trackback system to generate phishing profile using Maximum Dependency Algorithm (MDA). Phishing emails are split into group of phishers constructed by the MDA algorithm. Then, the forensic analysis is implemented to identify the type of phisher against already assumed group of attacker either single or collaborative attacker. The performance of the proposed strategy is tested on email-born phishing. The result shows that the dynamic strategy could be used for tracking and classifying the attacker. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-51281-5_27 | RECENT ADVANCES ON SOFT COMPUTING AND DATA MINING |
Keywords | Field | DocType |
Phishing,Trackback strategy,Forensic,Maximum Dependency Algorithm,Clustering | Trackback,Phishing,Feature selection,Computer science,Algorithm,Artificial intelligence,Cluster analysis,Machine learning | Conference |
Volume | ISSN | Citations |
549 | 2194-5357 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Isredza Rahmi A. Hamid | 1 | 32 | 3.75 |
| Noor Azah Samsudin | 2 | 15 | 4.54 |
| Aida Mustapha | 3 | 90 | 26.18 |
| Nureize Arbaiy | 4 | 25 | 9.78 |