Abstract
The Internet of Things paradigm is about to emerge in full scale but various security vulnerabilities are still to be addressed. One of these is the threat of Sybil attacks. A Sybil attacker creates and controls more than one identity on its physical device. These illegitimate identities of the Sybil attacker may be used for numerous malicious activities without the fear of being detected and hence accountable for committed malign actions. One of the promising countermeasures of Sybil attacks is received signal strength based localization and detection systems. However, these schemes detect only the direct Sybil attackers, where no collusion among the identities is assumed; and these schemes also incur overhead in the form of periodic and persistent localization. In this paper, we propose a detection system that detects both direct and indirect Sybil identities using one-time localization without causing overhead in the form of period localization information dissemination. The analysis of our scheme shows that the incurred overhead is significantly low in terms of communication, storage, and computation.
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Abbas, S. (2019). An Efficient Sybil Attack Detection for Internet of Things. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) New Knowledge in Information Systems and Technologies. WorldCIST'19 2019. Advances in Intelligent Systems and Computing, vol 931. Springer, Cham. https://doi.org/10.1007/978-3-030-16184-2_33
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DOI: https://doi.org/10.1007/978-3-030-16184-2_33
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