Identifying phishing attacks in communication networks using URL consistency features. (12th March 2020)

• Record Type: Journal Article
• Authors: Azeez, Nureni Ayofe; Salaudeen, Balikis Bolanle; Misra, Sanjay; Damaševičius, Robertas; Maskeliūnas, Rytis
• Is Part Of: International journal of electronic security and digital forensics. Volume 12:Number 2(2020)
• Page Start: 200
• Page End: 213
• Publication Date: 2020-03-12
• Subjects: phishing attacks -- risk assessment -- cybersecurity -- digital forensics -- digital evidence; Computer crimes -- Periodicals; Computer crimes -- Investigation -- Periodicals; Computer security -- Periodicals; Electronic commerce -- Law and legislation -- Periodicals; Information warfare -- Periodicals; 005.805
• Languages: English
• ISSNs: 1751-911X

Abstract

Phishing is a fraudulent attempt by cybercriminals, where the target audience is addressed by a text message, phone call or e-mail, requesting classified and sensitive information after presenting himself/herself as a legitimate agent. Successful phishing attack may result into financial loss and identity theft. Identifying forensic characteristics of phishing attack can help to detect the attack and its perpetuators and as well as to enable defence against it. To shield internet users from phishing assaults, numerous anti-phishing models have been proposed. Currently employed techniques to handle these challenges are not sufficient and capable enough. We aim at identifying phishing sites in order to guard internet users from being vulnerable to any form of phishing attacks by verifying the conceptual and literal consistency between the uniform resource locator (URL) and the web content. The implementation of the proposed PhishDetect method achieves an accuracy of 99.1%; indicating that it is effective in detecting various forms of phishing attacks.