Paper Info
Title
Multi-factor combination authentication using fuzzy graph domination model
Abstract
Superior to single-factor authentication, multi-factor authentication (MFA) provides enhanced security by requiring at least two factors to authenticate an entity. It has been studied extensively in recent years and has been applied to various fields. However, there is no adaptive and quantified method to evaluate the dynamic threats coming from different attacks. In this paper, we introduce fuzzy dominating set to model the multiple factors of privacy-preserving identities, and propose an adaptive MFA combinatorial model to achieve adaptive choosing one or multiple privacy-preserving identities to authenticate the user. Moreover, we propose an integer linear programming for solving the Fuzzy Domination Model, and propose a greedy algorithm for Fuzzy Domination (GFD) and a primal dual greedy algorithm for Fuzzy Domination (PDFD) based on this integer linear programming. This work will reduce the gap between dynamic MFA and its practice applications. Finally, the effectiveness and efficiency of both algorithms in MFA are analyzed and experimental results demonstrate that PDFD is comparatively efficient and effective for solving instances with moderate orders.
Year
DOI
Venue
2019
10.3233/JIFS-181859
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
Field
DocType
fuzzy dominating set,information security,multi-factor authentication,fuzzy graph theory
Authentication,Fuzzy graph,Theoretical computer science,Artificial intelligence,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
37
4.0
1064-1246
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Zehui Shao111930.98
Zepeng Li2209.07
Pu Wu322.79
Lanxiang Chen4124.66
Xiao-song Zhang530545.10