Continuous Implicit Authentication for Mobile Devices based on Adaptive Neuro-Fuzzy Inference System

Feng Yao, Suleiman Y. Yerima, BooJoong Kang, Sakir Sezer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)
285 Downloads (Pure)

Abstract

As mobile devices have become indispensable in modern life, mobile security is becoming much more important. Traditional password or PIN-like point-of-entry security measures score low on usability and are vulnerable to brute force and other types of attacks. In order to improve mobile security, an adaptive neuro-fuzzy inference system(ANFIS)-based implicit authentication system is proposed in this paper to provide authentication in a continuous and transparent manner.
To illustrate the applicability and capability of ANFIS in our implicit authentication system, experiments were conducted on behavioural data collected for up to 12 weeks from different Android users. The ability of the ANFIS-based system to detect an adversary is also tested with scenarios involving an attacker with varying levels of knowledge. The results demonstrate that ANFIS is a feasible and efficient approach for implicit authentication with an average of 95% user recognition rate. Moreover, the use of ANFIS-based system for implicit authentication significantly reduces manual tuning and configuration tasks due to its selflearning capability.
Original languageEnglish
Title of host publicationInternational Conference on Cyber Security and Protection of Digital Services (Cyber Security 2017): Proceedings
Publisher IEEE
Pages1-7
DOIs
Publication statusPublished - 19 Oct 2017
EventInternational Conference on Cyber Security and Protection of Digital Services (Cyber Security 2017) - London, United Kingdom
Duration: 19 Jun 201720 Jun 2017
http://c-mric.org/index.php/cs2017c

Conference

ConferenceInternational Conference on Cyber Security and Protection of Digital Services (Cyber Security 2017)
CountryUnited Kingdom
CityLondon
Period19/06/201720/06/2017
Internet address

Keywords

  • implicit authentication
  • mobile security
  • Adaptive neuro-fuzzy inference system
  • Authentication
  • behaviour based authentication

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  • Cite this

    Yao, F., Yerima, S. Y., Kang, B., & Sezer, S. (2017). Continuous Implicit Authentication for Mobile Devices based on Adaptive Neuro-Fuzzy Inference System. In International Conference on Cyber Security and Protection of Digital Services (Cyber Security 2017): Proceedings (pp. 1-7). IEEE . https://doi.org/10.1109/CyberSecPODS.2017.8074846