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Enhanced password processing scheme based on visual cryptography and OCR

Title
Enhanced password processing scheme based on visual cryptography and OCR
Authors
Yang D.Doh I.Chae K.
Ewha Authors
채기준도인실
SCOPUS Author ID
채기준scopus; 도인실scopusscopus
Issue Date
2017
Journal Title
International Conference on Information Networking
ISSN
1976-7684JCR Link
Citation
International Conference on Information Networking, pp. 254 - 258
Keywords
hashimage-based password schemevisual cryptography
Publisher
IEEE Computer Society
Indexed
SCOPUS scopus
Document Type
Conference Paper
Abstract
Traditional password conversion scheme for user authentication is to transform the passwords into hash values. These hash-based password schemes are comparatively simple and fast because those are based on text and famed cryptography. However, those can be exposed to cyber-Attacks utilizing password by cracking tool or hash-cracking online sites. Attackers can thoroughly figure out an original password from hash value when that is relatively simple and plain. As a result, many hacking accidents have been happened predominantly in systems adopting those hash-based schemes. In this work, we suggest enhanced password processing scheme based on image using visual cryptography (VC). Different from the traditional scheme based on hash and text, our scheme transforms a user ID of text type to two images encrypted by VC. The user should make two images consisted of subpixels by random function with SEED which includes personal information. The server only has user's ID and one of the images instead of password. When the user logs in and sends another image, the server can extract ID by utilizing OCR (Optical Character Recognition). As a result, it can authenticate user by comparing extracted ID with the saved one. Our proposal has lower computation, prevents cyber-Attack aimed at hash-cracking, and supports authentication not to expose personal information such as ID to attackers. © 2017 IEEE.
DOI
10.1109/ICOIN.2017.7899514
ISBN
9781509051243
Appears in Collections:
인공지능대학 > 컴퓨터공학과 > Journal papers
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