TY  - JOUR
T1  - Websites Phishing Detectio Using URLs Tokens as a Discriminating Features
AU - Yahya Daeef, Ammar AU - Badlishah Ahmad, R. AU - Yacob, Yasmin 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 3
SP  - 513
EP  - 519
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.513.519
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.513.519
KW  - Phishing
KW  -legitimate
KW  -lexical features
KW  -URL tokens
KW  -statistical classifier
AB  - The Phishing detector must be wide scope to deal with the several strategies used to start the
phishing campaign and provides high speed detection to avoid user’s unsatisfactionby introducing large delay.
Consequently, this word presents wide scope and fast detection system by using URLs tokens as a
discriminating features without using any external or content features. The method based on analyzing the
percentage of the re-used tokens and the token overlap between phishing and legitimate URLs. This research
differs from other research by analyzes URLs collected from different sources and according to, this analysis,
a statistical classifier is built and the performance is evaluated to measure the technique effectiveness. The
results show that the dictionary of phishing tokens is smaller than the dictionary of legitimate tokens and the
token overlap between phishing and legitimate URLs is small. Also, the token overlap rate between different
phishing sources is more than compared with legitimate token overlap percentage. The average accuracy of 77%
is achieved by this technique.
ER  -