Name
Abstract | ||
|---|---|---|
Despite the growth of prevention techniques, phishing remains an important threat since the principal countermeasures in use are still based on reactive URL blacklisting. This technique is inefficient due to the short lifetime of phishing Web sites, making recent approaches relying on real-time or proactive phishing URLs detection techniques more appropriate. In this paper we introduce PhishScore, an automated real-time phishing detection system. We observed that phishing URLs usually have few relationships between the part of the URL that must be registered (upper level domain) and the remaining part of the URL (low level domain, path, query). Hence, we define this concept as intra-URL relatedness and evaluate it using features extracted from words that compose a URL based on query data from Google and Yahoo search engines. These features are then used in machine learning based classification to detect phishing URLs from a real dataset. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CNSM.2014.7014140 | Network and Service Management |
Keywords | Field | DocType |
Web sites,computer crime,feature extraction,learning (artificial intelligence),pattern classification,query processing,search engines,Google search engine,PhishScore,Yahoo search engine,automated real-time phishing detection system,feature extraction,machine learning based classification,phishers minds hacking,phishing Web site short lifetime,prevention techniques,proactive phishing URL detection technique,query data,reactive URL blacklisting,real-time phishing URL detection technique | World Wide Web,Phishing,Computer science,Hacker,Blacklisting,Semantic URL,Spoofed URL,Phishing detection | Conference |
ISSN | Citations | PageRank |
2165-9605 | 7 | 0.50 |
References | Authors | |
22 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Samuel Marchal | 1 | 146 | 11.72 |
| Jerome Francois | 2 | 57 | 4.39 |
| Radu State | 3 | 623 | 86.87 |
| Thomas Engel | 4 | 538 | 59.08 |