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Securing ZigBee Communications Against Constant Jamming Attack Using Neural Network
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AI
DOI：10.1109/JIOT.2020.3034128.png)
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摘要
En 中文
ZigBee is a wireless communication technology that has been widely used to provide low-bandwidth wireless services for Internet-of-Things applications, such as building automation, medical data collection, and industrial equipment control. As ZigBee operates in the industrial, scientific and medical radio frequency bands, it may suffer from unintentional interference from coexisting radio devices (e.g., WiFi and Bluetooth) and/or radio jamming attacks from malicious devices. Although many results have been produced to enhance ZigBee security, there is no technique that can secure ZigBee against jamming attack. In this article, we propose a new ZigBee receiver by leveraging MIMO technology, which is capable of decoding its desired signal in the presence of constant jamming attack. The enabler is a learning-based jamming mitigation method, which can mitigate the unknown interference using an optimized neural network. We have built a prototype of our proposed ZigBee receiver on a wireless testbed. Experimental results show that it is capable of decoding its packets in the face of 20-dB stronger jamming. The proposed ZigBee receiver offers an average of 26.7-dB jamming mitigation capability compared to off-the-shelf ZigBee receivers.
Keyword:
Zigbee
Jamming
Interference
Receivers
Wireless fidelity
Wireless communication
Neural networks
Internet-of-Things (IoT) communications
jamming and anti-jamming attack
physical-layer security
ZigBee networks
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期刊
IF:
8.9
论文数:
1.4W
被引数:
7.8W
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