Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/692
Title: Defending against phishing attacks: taxonomy of methods, current issues and future directions
Authors: Gupta, B. B.
Arachchilage, Nalin A. G.
Psannis, Kostas E.
Type: Article
Subjects: FRASCATI::Engineering and technology
FRASCATI::Engineering and technology::Electrical engineering, Electronic engineering, Information engineering
Keywords: Machine learning
Social engineering
Data mining
Phishing
Security
Malware
Issue Date: 2018
Source: Telecommunication Systems
Volume: 67
Issue: 2
First Page: 247
Last Page: 267
Abstract: Internet technology is so pervasive today, for example, from online social networking to online banking, it has made people’s lives more comfortable. Due the growth of Internet technology, security threats to systems and networks are relentlessly inventive. One such a serious threat is “phishing”, in which, attackers attempt to steal the user’s credentials using fake emails or websites or both. It is true that both industry and academia are working hard to develop solutions to combat against phishing threats. It is therefore very important that organisations to pay attention to end-user awareness in phishing threat prevention. Therefore, aim of our paper is twofold. First, we will discuss the history of phishing attacks and the attackers’ motivation in details. Then, we will provide taxonomy of various types of phishing attacks. Second, we will provide taxonomy of various solutions proposed in literature to protect users from phishing based on the attacks identified in our taxonomy. Moreover, we have also discussed impact of phishing attacks in Internet of Things (IoTs). We conclude our paper discussing various issues and challenges that still exist in the literature, which are important to fight against with phishing threats.
URI: https://doi.org/10.1007/s11235-017-0334-z
https://ruomo.lib.uom.gr/handle/7000/692
ISSN: 1018-4864
1572-9451
Other Identifiers: 10.1007/s11235-017-0334-z
Appears in Collections:Department of Applied Informatics

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