Password Strength Tester

May 2023
Vol-9, Issue-3
Paper ID: 20152
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
Computer Science Engeneering
Keywords
Strength Encrptation
Abstract
Abstract—It is a well known fact that user-chosen passwords are somewhat predictable: by using tools such as dictionaries or probabilistic models, attackers and password recovery tools can drastically reduce the number of attempts needed to guess a password. Quite surprisingly, however, existing literature does not provide a satisfying answer to the following question: given a number of guesses, what is the probability that a state-of-the-art attacker will be able to break a password? To answer the former question, we compare and evaluate the effectiveness of currently known attacks using various datasets of known passwords. We find that a “diminishing returns” principle applies: in the absence of an enforced password strength policy, weak passwords are common; on the other hand, as the attack goes on, the probability that a guess will succeed decreases by orders of magnitude. Even extremely powerful attackers won’t be able to guess a substantial percentage of the passwords. The result of this work will help in evaluating the security of authentication means based on user-chosen passwords, and our methodology for estimating password strength can be used as a basis for creating more effective proactive password checkers for users and security auditing tools for administrators.

Author Information

# Name Institute / Affiliation
1 Raj Singh Galogotias University
2 Harsh Kumar Kashera Galogotias University

How to Cite

Use the following formats to cite this article in your research.

APA Style
Singh, Raj & Kashera, Harsh Kumar (2023). Password Strength Tester. International Journal of Advance Research and Innovative Ideas In Education, 9(3), 861-872.
MLA Style
Singh, Raj, and Harsh Kumar Kashera. "Password Strength Tester." International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 3, 2023, pp. 861-872.
IEEE Style
Raj Singh and Harsh Kumar Kashera, "Password Strength Tester," International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 3, pp. 861-872, 2023.
Vancouver Style
Singh Raj, Kashera Harsh Kumar. Password Strength Tester. International Journal of Advance Research and Innovative Ideas In Education. 2023;9(3):861-872.
Harvard Style
Singh, Raj & Kashera, Harsh Kumar (2023) 'Password Strength Tester', International Journal of Advance Research and Innovative Ideas In Education, 9(3), pp. 861-872.
Chicago Style
Singh, Raj and Harsh Kumar Kashera. "Password Strength Tester." International Journal of Advance Research and Innovative Ideas In Education 9, no. 3 (2023): 861-872.
Turabian Style
Singh, Raj and Harsh Kumar Kashera. "Password Strength Tester." International Journal of Advance Research and Innovative Ideas In Education 9, no. 3 (2023): 861-872.

Export Citation

Related Research

CYBERSECURITY WITH AI
SAHANA MURTHY 2026 Computer Science
PDF Unavailable
A NOVEL HYBRID IMAGE STEGANOGRAPHY TECHNIQUE BASED ON LSB AND CRYPTOGRAPHIC SECURITY
Pankaj Nandan et al. 2026 Computer Science
PDF Unavailable
AnimalAid AI: A Deep Learning Powered Early Warning System for Detecting Skin Infections and Diseases in Stray Dogs
Sharan Subhas Savalagi et al. 2026 Computer Science and Engineering
PDF Unavailable
LiverCare AI: Intelligent Medical Imaging Platform for Liver Tumor Detection and Clinical Guidance
Sheshank et al. 2026 Computer Science and Engineering
PDF Unavailable