Intelligent authentication system using graphical one-time passwords

Adarsha Sigdel, Kheng Cher Yeo, Yassine Maleh, Mamoun Alazab

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Conventional alphanumerical passwords have been the most common authentication medium for years; however, it is plagued by a fundamental problem: secure strong passwords are hard to create and remember, leading to insecure practices. There have been several studies proposing alternatives to replace alphanumerical passwords. However, such alternatives have not reached mainstream usage or widespread application. Our study has reviewed several authentication schemes and found that graphical authentication can be an alternative solution, leveraging visual components instead of text and taking advantage of the human mind's ability to remember graphical and positional information. Our study conducts an in-depth analysis of the existing graphical passwords and presents a graphical one-time-password (OTP) scheme as a replacement for alphanumerical passwords. The proposed one-time graphical password is built upon the user remembering their four preselected picture passwords displayed on a random 4×4 matrix and entering the (x,y) coordinate of the picture password on the matrix. Several different categories of picture passwords are provided, with the authentication matrix displaying decoy images along with the picture passwords. An in-depth analysis of the security, memorability and usability aspects is presented to show that our graphical OTP scheme can successfully thwart common graphical password attacks (such as shoulder-surfing and dictionary attacks). We also demonstrate that the proposed graphical authentication system can protect against various known attacks and satisfies different criteria as a replacement for alphanumerical passwords.
Original languageEnglish
Title of host publicationArtificial Intelligence for Biometrics and Cybersecurity
Subtitle of host publicationTechnology and applications
EditorsAhmed A. Abd El-Latif, Mohammed Adel Hammad, Yassine Maleh, Brij B. Gupta, Wojciech Mazurczyk
Place of PublicationLondon
PublisherInstitution of Engineering and Technology
Number of pages18
ISBN (Electronic)9781839535482
ISBN (Print)9781839535475
Publication statusPublished - Oct 2023


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