URL Scrutiny to Circumvent Phishing. (November 2019)

• Record Type: Journal Article
• Authors: Mahalakshmi, P.; Motwani, Bharat; Bajpai, Akhil
• Is Part Of: Journal of physics. Volume 1362(2019)
• Publication Date: 2019-11
• Subjects: Clustering -- Classification -- Apriori -- Tokens -- Neural Network -- Firefly; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1362/1/012126
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Increasing the number of cyber-crimes and frauds it has become the need of hour to seriously consider the threat and make some solid security arrangement against it. The links or Uniform Resource locator (URL) can be classified as benign, spam or malicious thus informing the user beforehand about its safety. As emails are hook to attach malicious URL, luring to catch the users. Malicious URL are the most common tool used in breaking identity and attacking either the system database or some financial frauds. Instead of focusing the source of such links if the rigorous testing on various attributes is performed on the URL itself using Random forest algorithm for threat detection and Support Vector Machine (SVM) to consider even the extreme cases is expected to improve the coverage and thus can provide the system user with high level security from counterfeited URL.