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LaSa: Location Aware Wireless Security Access Control for IoT Systems

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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.

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Acknowledgment

This work is supported by “the Fundamental Research Funds for the Central Universities” with No. DUT17LAB16, No. DUT2017TB02. This work is also (partially) supported by Tianjin Key Laboratory of Advanced Networking (TANK), School of Computer Science and Technology, Tianjin University, Tianjin China, 300350 and by Open fund of State Key Laboratory of Acoustics (No. SKLA201706).

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Authors and Affiliations

  1. Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of Software Dalian University of Technology, Dalian, China

    Bingxian Lu, Lei Wang, Jialin Liu, Wei Zhou & Linlin Guo

  2. The Department of Civil Engineering, Chosun University, Gwangju, Republic of Korea

    Myeong-Hun Jeong

  3. Geography and Geographic, Information Science, CyberGIS Center for Advanced, Digital and Spatial Studies, National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, USA

    Shaowen Wang

  4. College of Internet of Things Engineering, Hohai University, Changzhou, China

    Guangjie Han

  5. State Key Laboratory of Acoustics, Institute of Acoustics Chinese Academy of Sciences, Beijing, China

    Guangjie Han

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  1. Bingxian Lu
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  2. Lei Wang
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  3. Jialin Liu
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  4. Wei Zhou
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  5. Linlin Guo
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  6. Myeong-Hun Jeong
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  7. Shaowen Wang
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  8. Guangjie Han
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Correspondence to Lei Wang or Guangjie Han.

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Lu, B., Wang, L., Liu, J. et al. LaSa: Location Aware Wireless Security Access Control for IoT Systems. Mobile Netw Appl 24, 748–760 (2019). https://doi.org/10.1007/s11036-018-1088-x

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  • DOI: https://doi.org/10.1007/s11036-018-1088-x

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