Mobile Phishing Websites Detection and Prevention Using Data Mining Techniques

Mobile Phishing Websites Detection and Prevention Using Data Mining Techniques
Student’s name
Institution Affiliation(s)

Explain the principle contribution of the paper or the subject discussed in it (if any).
The principle contribution of the paper is mobile phishing websites. The paper describes
phishing as the process of trying to steal user data over the internet by posing as trusted entities
and thus gaining illegal or unauthorized access to victim’s user data such as usernames,
passwords, and credit card credentials (Kadhim, Al-saedi, & Al-Hassani, 2019).
Explain the technique presented in the paper (if any).
The paper describes several methods that are used for the detection of phishing, for
instance, heuristic methods, the blacklist techniques, and the visual appearance techniques. The
blacklist techniques checks websites in a list of all the websites that have been blacklisted.
Firstly, the blacklist method is advantageous and effective as it detects blacklisted sites
very fast. On the downside, the technique is not able to detect websites that appear only for a few
hours, a day, or “zero-day phishing attack”(Kadhim et al., 2019).
Secondly, the heuristic method depends on the characteristics extracted from HTML,
URL, and Search Engine, together with the data mining methods that are applied in determining
the status of the site. Thus, this method is preferable to blacklist techniques as it addresses the
zero-day phishing attacks (Goel & Jain, 2018).
Lastly, the visual appearance technique is dependent on the similarity between sites in the
detection of phishing. When the visual features of the suspected site match with the legit website,
the method checks if the URL is in the authentic domain URLs list. If it’s not found in the list,
then it is marked as a phishing website(Kadhim et al., 2019).
If there is an experiment, explain the setup first so that the obtained results can be better
appreciated.

The paper has an experiment, which is a proposed system called “Phishield.” The experiment is
taken in four stages which include;
a) System database checking is where the system built by the detection system, checks if the
site is already checked and minimize time and resource consuming.
b) Checking if the domain name is an IP
c) Feature extraction
d) Classify and predict if a website is phishing or not – This step is then followed by the
system taking proper action on the site.
The results of the experiment, according to the paper, showed that the system effectiveness in
predicting phishing websites with 97% as prediction accuracy.

References
Goel, D., & Jain, A. K. (2018). Mobile phishing attacks and defence mechanisms: State of art
and open research challenges. Computers & Security, 73, 519–544.
https://doi.org/10.1016/j.cose.2017.12.006
Kadhim, H. Y., Al-saedi, K. H., & Al-Hassani, M. D. (2019). Mobile Phishing Websites
Detection and Prevention Using Data Mining Techniques. International Journal of
Interactive Mobile Technologies (IJIM), 13(10), 205–214.
https://doi.org/10.3991/ijim.v13i10.10797