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Use of Input Distance Metric to implement fuzzy password matching

IP.com Disclosure Number: IPCOM000241184D
Publication Date: 2015-Apr-02
Document File: 2 page(s) / 37K

Publishing Venue

The IP.com Prior Art Database

Abstract

Current password based authentication schemes typically lean towards an all-or-nothing approach. This is fine in many situations, such as on-line banking, where strict security is required. Yet, there are other situations where lower security is acceptable and even desirable in terms of usability and availability. This core of this invention is the use of input distance based fuzzy password matching to improve usability and availability in certain security situations without necessarily reducing security risk.

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Use of Input Distance Metric to implement fuzzy password matching

Current password based authentication schemes typically lean towards an all-or-nothing approach. This is fine in many situations, such as on-line banking,

where strict security is required. Yet, there are other situations where lower security is acceptable and even desirable in terms of usability and availability. For example, a parental PIN code on a television or an on-line registration password for a free email newsletter. This core of this invention is the use of input distance based fuzzy password matching to improve usability and availability in certain security situations

without necessarily reducing security risk.

Similar to Hamming Distance and Levenshtein Distance, we define Input Distance as a metric to numerically identify the number and degree of input mistakes between two strings for a given input device. For example, characters represented by adjacent keys on a given keyboard would have an input distance of 1 (e.g. inputdistance("a","s")==1) for a US keyboard, characters represented by adjacent to adjacent keys would have an input distance of 2 (e.g., inputdistance("a","d")==2). Input distance need not be an integer. For example, since horizontally and vertically adjacent keys are easier mistype than diagonally adjacent keys, then perhaps, an immediately diagonally adjacent key could be considered to have an input distance of 0.9 rather than 1. (This concept is particularly evident when considering the keys on a numerical key pad.

(A key difference between other distance calculations including Hamming Distance, Levenshtein Distance, and fuzzy extractors is that Input Distance takes the input method and likelihood of various types human error in account to determine the distance. To emphasize the uniqueness of Input Difference, Hamming Distance, Levenshtein Distance, and fuzzy extractors would consider distance("pass","pas...