NoFish; Total Anti-Phishing Protection System

R.A.H.Devdunie Pabasara; Dhanushka Niroshan Atimorathanna; Tharindu Shehan Ranaweera; Jayani Rukshila Perera

NoFish; Total Anti-Phishing Protection System

R.A.H.Devdunie Pabasara * §

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Dhanushka Niroshan Atimorathanna

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Tharindu Shehan Ranaweera

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Jayani Rukshila Perera

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§ Sri Lanka Institute of Information Technology

NoFish; Total Anti-Phishing Protection System

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Abstract

Phishing attacks have been identified by researchers as one of the major cyber-attack vectors which the general public has to face today. Although software companies launch new anti-phishing products, these products cannot prevent all the phishing attacks. The proposed solution, “No Fish” is a total anti-phishing protection system created especially for end-users as well as for organizations. In this paper, a realtime anti-phishing system, which has been implemented using four main phishing detection mechanisms, is proposed. The system has the following distinguishing properties from related studies in the literature: language independence, use of a considerable amount of phishing and legitimate data, real-time execution, detection of new websites, detecting zero-hour phishing attacks and use of feature-rich classifiers, visual image comparison, DNS phishing detection, email client plug in and specially the overall system has designed to the levelbased security architecture to reduce the time-consumption.

References

22 Cites in Article

Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

R.A.H.Devdunie Pabasara, Dhanushka Niroshan Atimorathanna, Tharindu Shehan Ranaweera, Jayani Rukshila Perera. 2020. "NoFish; Total Anti-Phishing Protection System". Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 20 (GJCST Volume 20 Issue E3).

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GJCST Volume 20 Issue E3

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

GJCST-E Classification D.4.6

Submission ReceivedDecember 10, 2019
Peer Review Double Blind
Handling Editor
Accepted January 1, 2020
Published January 15, 2020

Version of record

v1.2

Issue date

December 5, 2020

Language

English

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Article Matrices

Total Score: 144

Country: Unknown

Subject: Global Journal of Computer Science and Technology

Authors: R.A.H.Devdunie Pabasara, Dhanushka Niroshan Atimorathanna, Tharindu Shehan Ranaweera, Jayani Rukshila Perera (PhD/Dr. count: 0)

View Count (all-time): 461

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Publish Date: 2020 01, Wed

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Total Views: 1.3K

Total Downloads: 77

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