• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.387-390
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• 2009

Wireless Sensor Network (WSN) can easily compromised from attackers because it has the limited resource and deployed in exposed environments. When the sensitive packets are occurred such as enemy's movement or fire alarm, attackers can selectively drop them using a compromised node. It brings the isolation between the basestation and the sensor fields. To detect selective forwarding attack, Xiao, Yu and Gao proposed checkpoint-based multi-hop acknowledgement scheme (CHEMAS). The check-point nodes are used to detect the area which generating selective forwarding attacks. However, CHEMAS has static probability of selecting check-point nodes. It cannot achieve the flexibility to coordinate between the detection ability and the energy consumption. In this paper, we propose the control method for the number fo check-point nodes. Through the control method, we can achieve the flexibility which can provide the sufficient detection ability while conserving the energy consumption.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.73-80
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• 2010

A wireless sensor network which is deployed in hostile environment can be easily compromised by attackers. The selective forwarding attack can jam the packet or drop a sensitive packet such as the movement of the enemy on data flow path through the compromised node. Xiao, Yu and Gao proposed the checkpoint-based multi-hop acknowledgement scheme(CHEMAS). In CHEMAS, each path node enable to be the checkpoint node according to the pre-defined probability and then can detect the area where the selective forwarding attacks is generated through the checkpoint nodes. In this scheme, the number of hops is very important because this parameter may trade off between energy conservation and detection capacity. In this paper, we used the fuzzy rule system to determine adaptive threshold value which is the number of hops for the ACK packets. In every period, the base station determines threshold value while using fuzzy logic. The energy level, the number of compromised node, and the distance to each node from base station are used to determine threshold value in fuzzy logic.