Toward Data Authenticity and Integrity for Blockchain-Based Mobile Edge Computing

Blockchain-based mobile edge computing (BMEC) solves the problem of limited computing resources of devices in the Internet of Things (IoT). However, there are some security threats in the blockchain environment, among which the attacks against consensus algorithms are particularly serious, such as d...

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Veröffentlicht in:IEEE sensors journal 2022-05, Vol.22 (10), p.9967-9980
Hauptverfasser: Ma, Tianchen, Du, Bowen, Li, Mianhong, Li, Jiangfeng, Shi, Yang, Fan, Hongfei
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Sprache:eng
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Zusammenfassung:Blockchain-based mobile edge computing (BMEC) solves the problem of limited computing resources of devices in the Internet of Things (IoT). However, there are some security threats in the blockchain environment, among which the attacks against consensus algorithms are particularly serious, such as double-spending attacks and long-range attacks. These attacks target the block proposal or validation process, which compromise the integrity of the BMEC by overwriting the correct block record with the wrong block record. In this article,we propose a scheme to solve the above problem by using the cooperative threshold signature and group management scheme to protect the block validity. The blockchain process of a single node is controlled in a group cooperative way, and each new block is regarded as a valid block only if it has a valid threshold signature for the group to which it belongs. Concretely, the system is initialized by a cooperative distributed key generation protocol, the device management protocol uses a resident node to ensure the security and efficiency of device join and leave, and the signature issuing protocol can tolerate a certain degree of exceptions of nodes within the group. We analyze the resistance ability of the scheme against consensus attacks, prove the security of the scheme, and analyze the computing and communication efficiency. Experimental evaluations on the protocols of the proposed scheme have been conducted on cloud virtual machines and embedded boards, including Raspberry Pi and UP2 Grove, which indicated that the scheme is efficient in practical scenarios.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2022.3163915