Linguistic Profiles in Biometric Security System for Online User Authentication

被引：0

作者：

Tumpa, Sanjida Nasreen ^{[1
]}

Gavrilova, Marina ^{[1
]}

机构：

[1] Univ Calgary, Dept Comp Sci, Calgary, AB, Canada

来源：

2020 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC) | 2020年

关键词：

Decision Support System; Biometric security; Intelligent Adaptive Systems (IAS); Risk analysis; Social Behavioral Biometric (SBB); Cognitive systems; Linguistic model; RECOGNITION; DEVICES;

D O I：

10.1109/smc42975.2020.9282937

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

A typical biometric system aims to recognize individuals based on their unique physiological or behavioral traits. Online Social Networking (OSN) platforms have become an integral part of the daily life of individuals, where they leave a recognizable trail of behavioral information. Social Behavioral Biometric (SBB), being an emerging trend, focuses on such trails to distinguish between individuals. This research investigates the impact of users' writing profiles on OSN to conclude whether such profiles contribute to SBB. The distinctiveness of the SBB features that are extracted from the social behavioral data of Twitter is studied. A person identification system that relies on the writing profiles of OSN users is proposed. The developed system is cross-validated on a social interaction database of 241 Twitter users. The rank-1 identification rate from users' writing profiles is 91.70% and the rank-8 identification rate is 99%. Furthermore, the experimental results establish that the users' writing profiles have the highest impact over other social biometric features.

引用

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页码：1033 / 1038

页数：6

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