Privacy-aware detection framework to mitigate new-age phishing attacks. (December 2021)

• Record Type: Journal Article
• Authors: Bhardwaj, Akashdeep; Al-Turjman, Fadi; Sapra, Varun; Kumar, Manoj; Stephan, Thompson
• Is Part Of: Computers & electrical engineering. Volume 96:Part A(2021)
• Publication Date: 2021-12
• Subjects: Social engineering -- Credential harvesting -- Privacy protection -- Phishing Framework -- Internet of Things -- Secure DNS; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2021.107546
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Proposed new three-phase framework to detect and mitigate new-age phishing attacks by Cyber-criminals, adopting sophisticated tactics. Implemented Python-based lightweight secure DNS infrastructure framework on user systems and IoT devices. Proposed unique phishing taxonomy that classifies phishing attacks based on new-age major methods being adopted by the cyber attackers. Abstract: End users and imperfectly configured Internet of Things devices are the weakest links and present low-hanging targets to attack. In workplaces, online work and business are performed over insecure internet. Phishing presents privacy and safety threats to the personal credentials and identity of unsuspecting victims. Unaware untrained users end up as the main targets for the simplest methods of stealing credentials, identities, and personal details. Clever attackers do not just depend on tools and technologies; they have increased the use of targeted Phishing as the new-age attack vector. With increasing users and devices, attackers resort to building one-to-one relationships with unsuspecting victims. The authors present a new privacy-aware framework to detect and mitigate Phishing attacks against new-age tactics to achieve maximum impact against unsuspecting victims and the Internet of things. The authors proposed unique Phishing taxonomy. Results show the proposed framework is capable of identifying multiple Phishing attacks.