## 2 Related Work
In BIOSARP, the AIS begins to check neighboring node behavior and to execute the classification process only once the neighbor table is populated because the AIS depends on the routing table information. Until the AIS-based preventive measure is initiated, adversaries have an opportunity to seize control of the entire deployed network. [PERSON] _et al._[18] presented a method that can detect dynamic and static wormhole attacks in geographic routing protocols (DWGRP). DWGRP depends on a pairwise key pre-distribution scheme with the assistance of beacon packets. When a node is initialized, the beacon packets of the new structure are broadcast, and a neighbor table is generated in reply. The authors conducted an ns-2-based simulation to evaluate DWGRP in terms of the probability of missed detection, wormhole detection rate, and resend packet rate. However, DWGRP has several drawbacks. The main drawback is that when the beacon packets are broadcast, DWGRP sends out unencrypted information that can be easily hacked, thus compromising the entire network. Furthermore, in the simulation study, each node updated its neighborhood table every 0.3 s by broadcasting beacon packets. This behavior implies that the entire network will be busy updating neighbor tables essentially at all times; however, this is totally unrealistic and is itself a DDOS attack. In a WSN, numerous broadcasts cause battery life to decrease and collisions to occur, resulting in packet loss. Hence, the underlying concept of DWGRP is not practical, and it is very costly because the nodes require a global positioning system (GPS). [PERSON] _et al._[PERSON] _et al._ (2016) proposed an elliptic curve cryptography-based secure energy-efficient access-control scheme. Their theoretical security analysis showed that the proposed mechanism addresses replay attacks, impersonation attacks, and sensor node spoofing attacks. In [PERSON] _et al._ (2016), the authors proposed the Double Cluster Heads Model (DCHM) based on clustering, trust systems, and data fusion. This model involves the selection of two cluster heads per cluster to perform data fusion independently. The authors claimed that the proposed algorithm detects and prevents attacks on a WSN based on the assumption that compromised cluster heads will generate random results and the outputs received from the two cluster heads will therefore differ. The proposed concept of a system based on reputation and trust depends on feedback (from the base station to the cluster heads) and information gathering, which generate packet overhead. Furthermore, the authors assumed that the base station is a trusted computing platform and that at the time of programming, every node will be assigned three keys, namely, a master key, a pairwise key and a cluster key. Among these three static keys, the cluster key is unique for each cluster, introducing considerable complexity in the programming and deployment of nodes. In their threat model, the authors considered attacks that mislead the user, namely, jamming, the falsification of local values, and the falsification of fusion results. In their performance evaluation, comparisons between compromised sensor nodes and credible sensor nodes were first conducted, and the DCHM results were then compared with those for BRSN [PERSON] _et al._ (2016) in terms of the security of data fusion, accuracy, and average energy consumption over the network lifetime. In [PERSON] _et al._ (2016), the authors proposed a scheme called Fully homomorphic Encryption based Secure data Aggregation (FESA) in large-scale wireless sensor networks (LWSNs) based on message authentication codes (MACs) to support arbitrary aggregation operations and provide end-to-end data confidentiality. This scheme involves complete data encryption and incurs increased computational overhead because of its large public key size. Therefore, it is not feasible, particularly for LWSNs.