Detecting Malicious and Compromised URLs in E-Mails Using Association Rule
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Date
2017
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Publisher
Covenant Journal of Informatics & Communication Technology
Abstract
The rate of cybercrime is on the rise as more people embrace
technology in their different spheres of live. Hackers are daily exploiting the
anonymity and speed which the internet offers to lure unsuspecting victims into
disclosing personal and confidential information through social engineering,
phishing mails and sites and promises of great rewards which are never
received. Thus resulting in great loss of property, finances, life, etc. and harm
to their victims. This research work seeks to evaluate ways of protecting users
from malicious Uniform Resource Locators (URLs) embedded in the emails
they receive. The aim is to evaluate ways of identifying malicious URLs in
emails by classifying them based on their lexical and hostname features. This
study is conducted by extracting features from URLs sourced from phishing
tank and DMOZ and adopting Association Rule of classification in building a
URL classifier that analyzed extracted features of a URL and use it in
predicting if it is malicious or not. 0.546 level of accuracy and an error rate of
0.484 was achieved as multiple URL features were employed in the
classification process.
Description
Keywords
Malicious, Association rule, URLs, Cybercrime, Hackers