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Evaluating the impact of malicious spoofing attacks on Bluetooth low energy based occupancy detection systems

Evaluating the impact of malicious spoofing attacks on Bluetooth low energy based occupancy detection systems

Oliff, William, Filippoupolitis, Avgoustinos and Loukas, George (2017) Evaluating the impact of malicious spoofing attacks on Bluetooth low energy based occupancy detection systems. In: 2017 IEEE 15th ACIS International Conference on Software Engineering Research, Management and Applications (SERA 2017). IEEE. ISBN 978-1-5090-5757-3 ISSN 978-1-5090-5756-6 (Online) (doi:https://doi.org/10.1109/SERA.2017.7965755)

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Abstract

Occupancy detection of a building has a wide range of applications. Areas such as emergency management, home automation and building energy management can benefit from the knowledge of occupants' locations to provide better results and improve their efficiency. Bluetooth Low Energy (BLE) beacons installed inside a building are able to provide information on an occupant's location. Since, however, their operation is based on broadcasting advertisements, they are vulnerable to network security breaches. In this work, we evaluate the effect of two types of spoofing attacks on a BLE based occupancy detection system. The system is composed of BLE beacons installed inside the building, a mobile application installed on occupants’ mobile phones and a remote control server. Occupancy detection is performed by a classifier installed on the remote server. We use our real-world experimental results to evaluate the impact of these attacks on the system's operation, particularly in terms of the accuracy with which it can provide location information.

Item Type: Conference Proceedings
Title of Proceedings: 2017 IEEE 15th ACIS International Conference on Software Engineering Research, Management and Applications (SERA 2017)
Additional Information: 15th IEEE/ACIS International Conference on Software Engineering Research, Management and Applications, 7th-9th June 2017, University of Greenwich, London, England
Uncontrolled Keywords: iBeacon, Bluetooth Low Energy, Occupancy Detection, Machine Learning, Malicious Spoofing Attacks
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Department of Computing & Information Systems
Related URLs:
Last Modified: 18 Sep 2017 09:41
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/16958

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