• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.393-401
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• 2024

Recently, the Internet of Things (IoT) has been widely used in industries and daily life that directly affect human safety, life, and assets. However, IoT devices, which need to meet low-cost, lightweight, and low-power requirements, face a significant problem of shortened battery lifetime due to battery draining attacks and interference. To solve this problem, the 802.11ba standard for the Wake-up Receiver (WuR) has emerged, this feature is playing a crucial role in minimizing energy consumption. However, the WuR protocol did not consider security mechanisms in order to reduce latency and overhead. Therefore, in this study, anAdaptive Power Saving Mechanism (APSM) is proposed for low-power WuR to counter battery draining attacks. APSM can minimize abnormally occurring power consumption by exponentially increasing power-saving time in environments prone to attacks. According to experimental results, the proposed APSM improved energy consumption efficiency by a minimum of 13.77% compared to the traditional Legacy Power Saving Mechanism (LPSM) when attack traffic ratio is 10% or more of the total traffic.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.197-200
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• 2008

In most sensor networks, nodes can be easily compromised by adversaries due to hostile environments. Adversaries may use compromised nodes to inject false reports into the sensor networks. Such false report attacks will cause false alarms that can waste real-world response effort, and draining the finite amount of energy resource in the battery-powered network. A dynamic enroute scheme proposed by Yu and Guan can detect and drop such false reports during the forwarding phase. In this scheme, choosing a threshold value is very important, as it trades off between security power and energy consumption. In this paper, we propose a threshold determining method which uses the fuzzy rule-based system. The base station periodically determines a threshold value though the fuzzy rule-based system. The number of cluster nodes, the value of the key dissemination limit, and the remaining energy of nodes are used to determine the threshold value.