AcSIS: Authentication System Based on Image Splicing

Authors

  • S. Hamid Center for Computing Research, Jinnah University for Women, Pakistan
  • N. Z. Bawany Center for Computing Research, Jinnah University for Women, Pakistan
  • S. Khan Department of Computer Science, FAST National University of Computer and Emerging Sciences, Pakistan
Volume: 9 | Issue: 5 | Pages: 4808-4812 | October 2019 | https://doi.org/10.48084/etasr.3060

Abstract

Text-based passwords are widely used for the authentication of digital assets. Typically, password security and usability is a trade-off, i.e. easy-to-remember passwords have higher usability that makes them vulnerable to brute-force and dictionary attacks. Complex passwords have stronger security but poor usability. In order to strengthen the security in conjunction with the improved usability, we hereby propose a novel graphical authentication system. This system is a picture-based password scheme which comprises of the method of image splicing. Authentication data were collected from 33 different users. The usability of the method was evaluated via a comparison between the number of correct and incorrect authentication attempts and time taken. Additionally, a comparison was made between our proposed method and a complex text-based password authentication method using the authentication success rate. Authentication using image splicing proved to be resilient to brute-force attacks since the processing of images consumes a voluminous password space. The evaluation of the usability revealed that graphical passwords were easy-to-remember, resulting in a higher number of correct attempts. The proposed method produced 50% higher success rate compared to the text-based method. Findings motivate the use of the proposed method for securing digital assets.

Keywords:

secured authentication, brute force attack, graphical authentication, picture-based authentication, image splicing, graphical passwords

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How to Cite

[1]
S. Hamid, N. Z. Bawany, and S. Khan, “AcSIS: Authentication System Based on Image Splicing”, Eng. Technol. Appl. Sci. Res., vol. 9, no. 5, pp. 4808–4812, Oct. 2019.

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