A Brief Review of Phishing Detection and Prevention Methods
Prof. R.A. Khan
, Prasad Mahabare , Kanak Likhite , Makarand Raut , Swapnil Baviskar
Phishing attack, URL, Machine learning, Anti-phishing repositories, Social Engineering.
Cyber-attacks have become an international threat worldwide - confidential and secret data is being compromised which can harm national security. Two domains of the IT industry are majorly compromised which primarily consists of information processing and physical infrastructure supporting the first domain. Phishing is one of the most popular attacks that malicious groups carry out towards the general users. Phishing is the vindictive attempts to gain sensitive information like username, passwords, credit card information etc. which is often disguised as trustworthy source to the innocent users. When combined with Social engineering which often differs for different users, they may find very tempting to log in their credentials. This makes phishing one of the most dangerous and malignant attack. Although Phishing websites are very common, there are numerous methods to detect are prevent these attacks. These range from URL detection where a phishing website can be detected using some of the key features based on their Uniform Resource Locator to the use of Machine Learning Algorithms like Random Forest, Artificial Neural Network or Select Vector Method so that to stop these websites dynamically. There are also some methods that use Blacklist approach, where the system refers to anti-phishing repositories like Phishtank or Yahoo Phishing database to check whether the site is a phishing website or a legitimate one. This review paper explains many different methods used for the detection and prevention of phishing websites explaining the above-mentioned techniques in much more detail and also many other methods that help the users stay safe and secure from this type vicious attack.
"A Brief Review of Phishing Detection and Prevention Methods", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.3, Issue 11, page no.257 - 262, December-2018, Available :https://ijsdr.org/papers/IJSDR1812043.pdf
Volume 3
Issue 11,
December-2018
Pages : 257 - 262
Paper Reg. ID: IJSDR_180895
Published Paper Id: IJSDR1812043
Downloads: 000347240
Research Area: Engineering
Country: -, -, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
