TY - GEN
T1 - Secure indoor positioning against signal strength attacks via optimized multi-voting
AU - Li, Yunzhi
AU - Hu, Yidan
AU - Zhang, Rui
AU - Zhang, Yanchao
AU - Hedgpeth, Terri
N1 - Funding Information:
We would like to thank anonymous reviewers for their insightful comments that have helped improve the quality of this work. This work was supported in part by the US National Science Foundation under grants CNS-1700039, CNS-1651954 (CAREER), CNS-1718078, CNS-1514381, and CNS-1619251.
Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/6/24
Y1 - 2019/6/24
N2 - Indoor positioning systems (IPSes) can enable many location-based services in large indoor venues where GPS signals are unavailable or unreliable. Among the most viable types of IPSes, RSS-IPSes rely on ubiquitous smartphones and indoor WiFi infrastructures and explore distinguishable received signal strength (RSS) measurements at different indoor locations as their location fingerprints. RSSIPSes are unfortunately vulnerable to physical-layer RSS attacks that cannot be thwarted by conventional cryptographic techniques. Existing defenses against RSS attacks are all subject to an inherent tradeoff between indoor positioning accuracy and attack resilience. This paper presents the design and evaluation of MV-IPS, a novel RSS-IPS based on weighted multi-voting, which does not suffer from this tradeoff. In MV-IPS, every WiFi access point (AP) that receives a user's RSS measurement gives a weighted vote for every reference location, and the reference location that receives the highest accumulative votes from all APs is output as the user's most likely position. Trace-driven simulation studies based on real RSS measurements demonstrate that MV-IPS can achieve much higher positioning accuracy than prior solutions no matter whether RSS attacks are present.
AB - Indoor positioning systems (IPSes) can enable many location-based services in large indoor venues where GPS signals are unavailable or unreliable. Among the most viable types of IPSes, RSS-IPSes rely on ubiquitous smartphones and indoor WiFi infrastructures and explore distinguishable received signal strength (RSS) measurements at different indoor locations as their location fingerprints. RSSIPSes are unfortunately vulnerable to physical-layer RSS attacks that cannot be thwarted by conventional cryptographic techniques. Existing defenses against RSS attacks are all subject to an inherent tradeoff between indoor positioning accuracy and attack resilience. This paper presents the design and evaluation of MV-IPS, a novel RSS-IPS based on weighted multi-voting, which does not suffer from this tradeoff. In MV-IPS, every WiFi access point (AP) that receives a user's RSS measurement gives a weighted vote for every reference location, and the reference location that receives the highest accumulative votes from all APs is output as the user's most likely position. Trace-driven simulation studies based on real RSS measurements demonstrate that MV-IPS can achieve much higher positioning accuracy than prior solutions no matter whether RSS attacks are present.
KW - Fingerprint
KW - Indoor positioning
KW - RSS
KW - Security
KW - Signal strength attack
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U2 - 10.1145/3326285.3329068
DO - 10.1145/3326285.3329068
M3 - Conference contribution
AN - SCOPUS:85069161728
T3 - Proceedings of the International Symposium on Quality of Service, IWQoS 2019
BT - Proceedings of the International Symposium on Quality of Service, IWQoS 2019
PB - Association for Computing Machinery, Inc
T2 - 2019 International Symposium on Quality of Service, IWQoS 2019
Y2 - 24 June 2019 through 25 June 2019
ER -