Phishing Detection by determining reliability factor using rough set theory
This addresses phishing detection for online users, but it is incremental as it applies an existing method (rough set theory) to a known problem.
The paper tackles phishing detection by grouping thirteen factors into four strata and using rough set theory to compute a reliability factor that classifies sites as valid or fake, also identifying the most and least influential factors.
Phishing is a common online weapon, used against users, by Phishers for acquiring a confidential information through deception. Since the inception of internet, nearly everything, ranging from money transaction to sharing information, is done online in most parts of the world. This has also given rise to malicious activities such as Phishing. Detecting Phishing is an intricate process due to complexity, ambiguity and copious amount of possibilities of factors responsible for phishing . Rough sets can be a powerful tool, when working on such kind of Applications containing vague or imprecise data. This paper proposes an approach towards Phishing Detection Using Rough Set Theory. The Thirteen basic factors, directly responsible towards Phishing, are grouped into four Strata. Reliability Factor is determined on the basis of the outcome of these strata, using Rough Set Theory . Reliability Factor determines the possibility of a suspected site to be Valid or Fake. Using Rough set Theory most and the least influential factors towards Phishing are also determined.