LaSa: Location Aware Wireless Security Access Control for IoT Systems

Bingxian Lu, Lei Wang, Jialin Liu, Wei Zhou, Linlin Guo, Myeong Hun Jeong, Shaowen Wang, Guangjie Han

Research output: Contribution to journalArticle

Abstract

IoT (Internet of Things) security has become a severe yet not well solved problem attracting increasing research attention as well as industrial concerns. Location-based access control approaches, such as Wi-Fi geo-fencing, promise to fulfill the needs of preventing unauthorized access to IoT systems. We propose a crowdsourcing method for location aware security access control, namely LaSa, which is able to confine wireless network access inside certain physical areas only using a single commercial Access Point (AP). Specifically, LaSa detects whether a user enters or exits a room by discovering and recognizing the unique signal patterns. It combines the Received Signal Strength (RSS), Channel State Information (CSI), and coarse Angle of Arrival (AoA) data to improve the accuracy of user classification for accessing the wireless network. Real-world experimental results show that LaSa can achieve a 97.0% accuracy of identification of unauthorized users while maintaining a low false blocking rate of authorized users as low as 3.3%. LaSa is designed to be straightforward for integration with commercial APs and deployment to home and business Wi-Fi environments.

Original languageEnglish (US)
Pages (from-to)748-760
Number of pages13
JournalMobile Networks and Applications
Volume24
Issue number3
DOIs
StatePublished - Jun 15 2019

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Keywords

  • Access control
  • Internet of things
  • Machine learning
  • User validation

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications

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