A Scheme for Adaptively Countering Application Layer Security Attacks in Wireless Sensor Networks

Fuzzy-Based Adaptive Countering Method against False Data Injection Attacks in Wireless Sensor Networks

“…In general, the average velocity of each type of objects can be estimated. It is not easy to make non-existing objects moving using a few compromised nodes, so that objects moving very slowly could be a signature of FDIAs [4].…”

“…Compared to ACS [4], the method can reduce space complexity as well as the detection errors. Moreover, it can be optimized by GAOM, so that the users need not to determine threshold parameters for the detection.…”

“…However, in terms of energy saving, they all are inefficient under normal situations since such en-route verification processes involve extra communication and computation overhead [4]. Therefore, centralized solutions, such as the adaptive countering scheme (ACS) [4] and the fuzzy-based FDIAs detection (FFD) [6], have been recently proposed to minimize the energy consumption due to the verification processes. They detect FDIAs through the analysis of reports collected at BSs, so that forwarding nodes need not to verify the legitimacy of MACs.…”

“…To counter FDIAs, researchers have proposed security solutions [1]- [3] in which forged reports can be detected and discarded by forwarding nodes. However, especially under normal situations, these solutions are inefficient in terms of energy saving since they involve en-route verification processes [4].…”

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“…The technology of the sensor network easily and conveniently provides diverse information to users. However, the sensor network has the greatest probability of being captured and compromised because it operates in an open environment [3,4]. In addition, the sensor node is readily exposed to diverse attack patterns from malicious attackers.…”