J 2022

An Adaptive Anti-jamming System in HyperLedger-based Wireless Sensor Networks

MBAREK, Bacem, Mouzhi GE and Tomáš PITNER

Basic information

Original name

An Adaptive Anti-jamming System in HyperLedger-based Wireless Sensor Networks

Authors

MBAREK, Bacem (788 Tunisia, belonging to the institution), Mouzhi GE (156 China) and Tomáš PITNER (203 Czech Republic, belonging to the institution)

Edition

Wireless Networks, SPRINGER, 2022, 1022-0038

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 3.000

RIV identification code

RIV/00216224:14330/22:00125116

Organization unit

Faculty of Informatics

UT WoS

000744749300001

Keywords in English

Jamming attack; Wireless sensor networks; Data communications; Collaborative healthcare

Tags

International impact, Reviewed
Změněno: 28/3/2023 09:57, RNDr. Pavel Šmerk, Ph.D.

Abstract

V originále

Using new methodologies such as Blockchain in data communications in wireless sensor networks (WSN) has emerged owing to the proliferation of collaborative technologies. However, the WSN is still vulnerable to denial of service cyber attacks, in which jamming attack becomes prevalent in blocking data communications in WSN. The jamming attack launches malicious sensor nodes to block legitimate data communications by intentional interference. This can in turn cause monitoring disruptions, data loss and other safety-critical issues. In order to address the malicious attacks, this paper proposes an adaptive anti-jamming solution based on Hyperledger Fabric-based Blockchain, named as ABAS, to ensure the reliability and adaptivity of data communication in case of jamming attacks. In order to validate the ABAS solution, we applied the algorithm in healthcare WSN and showed that ABAS has significantly reduce the jamming coverage and energy consumption while maintaining high computational performance.