Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Conference Proceedings
Publisher : IEEE
Source : 2020 5th International Conference on Communication and Electronics Systems (ICCES)
Url : https://ieeexplore.ieee.org/abstract/document/9138011
Campus : Amritapuri
School : School of Computing
Center : Algorithms and Computing Systems
Year : 2020
Abstract : Passwords are as yet the prevailing path for user verification and system security while other validation techniques exist. So selecting a strong password is a challenging thing. Passwords are used in every walk of life like logging into a system, creating an account in an online store, banking, etc. People struggle to remember all of their passwords and so they prefer to use passwords based on their personal attributes viz.their name, spouse name, date of birth, etc. Choosing such passwords could be at the risk of being hacked. Generally the strength of passwords is checked based on the general guidelines like it should contain alphanumeric characters, special symbols, etc. But it never checks whether the chosen password is based on user attributes. Our proposed system checks the strength of passwords through segmentation algorithms and analyses whether the chosen password is based on user attributes and it is considered to be a weak password and strong if it is not based on user attributes. In this paper, an optimal segmentation algorithm named Password Segmentation Algorithm is proposed to segment password and user attributes, and later the correlation between a segmented password and user attributes is done. Passwords with less correlation of private details are the safest to use.
Cite this Research Publication : Sivapriya, K., and L. R. Deepthi. "Password strength analyzer using segmentation algorithms." 2020 5th International Conference on Communication and Electronics Systems (ICCES). IEEE, 2020.