TY - GEN
T1 - Practical bluetooth traffic sniffing
T2 - 14th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2016
AU - Albazrqaoe, Wahhab
AU - Huang, Jun
AU - Xing, Guoliang
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2016/6/20
Y1 - 2016/6/20
N2 - With the prevalence of personal Bluetooth devices, potential breach of user privacy has been an increasing concern. To date, sniffing Bluetooth traffic has been widely considered an extremely intricate task due to Bluetooth's indiscoverable mode, vendor-dependent adaptive hopping behavior, and the interference in the open 2.4 GHz band. In this paper, we present BlueEar - a practical Bluetooth traffic sniffer. BlueEar features a novel dual-radio architecture where two Bluetooth-compliant radios coordinate with each other on learning the hopping sequence of indiscoverable Bluetooth networks, predicting adaptive hopping behavior, and mitigating the impacts of RF interference. Experiment results show that BlueEar can maintain a packet capture rate higher than 90% consistently in real-world environments, where the target Bluetooth network exhibits diverse hopping behaviors in the presence of dynamic interference from coexisting 802.11 devices. In addition, we discuss the privacy implications of the BlueEar system, and present a practical countermeasure that effectively reduces the packet capture rate of the sniffer to 20%. The proposed countermeasure can be easily implemented on the Bluetooth master device while requiring no modification to slave devices like keyboards and headsets.
AB - With the prevalence of personal Bluetooth devices, potential breach of user privacy has been an increasing concern. To date, sniffing Bluetooth traffic has been widely considered an extremely intricate task due to Bluetooth's indiscoverable mode, vendor-dependent adaptive hopping behavior, and the interference in the open 2.4 GHz band. In this paper, we present BlueEar - a practical Bluetooth traffic sniffer. BlueEar features a novel dual-radio architecture where two Bluetooth-compliant radios coordinate with each other on learning the hopping sequence of indiscoverable Bluetooth networks, predicting adaptive hopping behavior, and mitigating the impacts of RF interference. Experiment results show that BlueEar can maintain a packet capture rate higher than 90% consistently in real-world environments, where the target Bluetooth network exhibits diverse hopping behaviors in the presence of dynamic interference from coexisting 802.11 devices. In addition, we discuss the privacy implications of the BlueEar system, and present a practical countermeasure that effectively reduces the packet capture rate of the sniffer to 20%. The proposed countermeasure can be easily implemented on the Bluetooth master device while requiring no modification to slave devices like keyboards and headsets.
UR - http://www.scopus.com/inward/record.url?scp=84979955955&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84979955955&origin=recordpage
U2 - 10.1145/2906388.2906403
DO - 10.1145/2906388.2906403
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781450342698
T3 - MobiSys 2016 - Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services
SP - 333
EP - 345
BT - MobiSys 2016 - Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services
PB - Association for Computing Machinery
Y2 - 25 June 2016 through 30 June 2016
ER -