Mobility profiling for user verification with anonymized location data

Miao Lin, Hong Cao, Vincent Zheng, Kevin Chen Chuan Chang, Shonali Krishnaswamy

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

Abstract

Mobile user verification is to authenticate whether a given user is the legitimate user of a smartphone device. Unlike the current methods that commonly require users active cooperation, such as entering a short pin or a one-stroke draw pattern, we propose a new passive verification method that requires minimal imposition of users through modelling users subtle mobility patterns. Specifically, our method computes the statistical ambience features on WiFi and cell tower data from location anonymized data sets and then we customize Hidden Markov Model (HMM) to capture the spatial-temporal patterns of each user's mobility behaviors. Our learned model is subsequently validated and applied to verify a test user in a time-evolving manner through sequential likelihood test. Experimentally, our method achieves 72% verification accuracy with less than a day's data and a detection rate of 94% of illegitimate users with only 2 hours of selected data. As the first verification method that models users' mobility pattern on location-anonymized smartphone data, our achieved result is significant showing the good possibility of leveraging such information for live user authentication.

Original languageEnglish (US)
Title of host publicationIJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence
EditorsMichael Wooldridge, Qiang Yang
PublisherInternational Joint Conferences on Artificial Intelligence
Pages960-966
Number of pages7
ISBN (Electronic)9781577357384
StatePublished - Jan 1 2015
Event24th International Joint Conference on Artificial Intelligence, IJCAI 2015 - Buenos Aires, Argentina
Duration: Jul 25 2015Jul 31 2015

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
Volume2015-January
ISSN (Print)1045-0823

Other

Other24th International Joint Conference on Artificial Intelligence, IJCAI 2015
CountryArgentina
CityBuenos Aires
Period7/25/157/31/15

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Lin, M., Cao, H., Zheng, V., Chang, K. C. C., & Krishnaswamy, S. (2015). Mobility profiling for user verification with anonymized location data. In M. Wooldridge, & Q. Yang (Eds.), IJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence (pp. 960-966). (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2015-January). International Joint Conferences on Artificial Intelligence.