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Linkcalculator – An Efficient Link-Based Phishing Detection Tool

Author

Listed:
  • Orunsolu Abiodun

    (Moshood Abiola Polytechnic Abeokuta, Ogun NIGERIA)

  • Sodiya A.S

    (Federal University of Agriculture, Abeokuta, South west NIGERIA.)

  • Kareem S.O

    (Moshood Abiola Polytechnic Abeokuta, Ogun NIGERIA)

Abstract

The problem of phishing attacks continues to demand new solutions as existing solutions are limited by various challenges such as high computational requirements, zero-day attacks, needs for updates, complex ruled-based, etc. Besides, the emerging mobile market demands simple solutions to phishing due to several factors such as memory, fragmentation, etc. In response to the above challenges, a simple anti-phishing tool called LinkCalculator is presented. The proposed LinkCalculator anti-phishing scheme is based on an algorithm designed to extract link characteristics from loading URLs to determine their legitimacy. Unlike the other link-based extraction approaches, the proposed approach introduced the concept of weight to represent the different links found in a URL. This is because certain link information within parsed webpages or requests is sufficient to classify them as phishing without loss of generality. The approach is experimented using a dataset of 300 instances consisting of 150 legitimate URLs and 150 phishing URLs from openly-available research datasets. The experimental results indicate a significance performance of 100%. True Negative Rate and 0.00% False Positive Rate for legitimate instances and True Positive Rate of 96.67% with 0.03 % False Negative Rate for phishing instances which indicate that the approach offers a more efficient lightweight approach to phishing detection.

Suggested Citation

  • Orunsolu Abiodun & Sodiya A.S & Kareem S.O, 2020. "Linkcalculator – An Efficient Link-Based Phishing Detection Tool," Acta Informatica Malaysia (AIM), Zibeline International Publishing, vol. 4(2), pages 37-44, October.
  • Handle: RePEc:zib:zbnaim:v:4:y:2020:i:2:p:37-44
    DOI: 10.26480/aim.02.2020.37.44
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