A Clone Detection Algorithm with Low Resource Expenditure for Wireless Sensor Networks

Zhong, Zhihua; Si, Luo; Zhu, Hongliang; Yang, Xin

doi:10.1155/2018/4396381

Cited by 5 publications

(5 citation statements)

References 17 publications

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“…Several clone node detection techniques and fault detection techniques have been proposed in the literature, with the majority of them focusing on the node's location, because each node in the network has a unique node id and spatial coordinates, and if two different nodes in the network claim the same node id but with different spatial coordinates, it clearly indicates the presence of a clone node and its attack. In [6] replication attacks were detected using nearby social signatures. Witness nodes [7] need more battery power, memory, energy, and other resources than normal nodes.…”

Section: Related Workmentioning

confidence: 99%

“…7. The consumption of energy of a node in a mobile network is defined as the sum of the processor energy (E P ), mobility energy (EMob), and transceiver energy (E Tr ) [16] which is represented in (6), where E C is defined as the total energy consumed and the energy of the processor is defined by (7) and where E Pzstate is the processor state energy consumption and E Pchange is the energy consumed in state transition. Transceiver energy consumption is defined by (8):…”

Section: Energy Consumptionmentioning

confidence: 99%

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Intelligent Multilevel Node Authentication in Mobile Computing Using Clone Node

Malhotra¹,

Bala²

2022

Computers, Materials &Amp; Continua

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Nodes in a mobile computing system are vulnerable to clone attacks due to their mobility. In such attacks, an adversary accesses a few network nodes, generates replication, then inserts this replication into the network, potentially resulting in numerous internal network attacks. Most existing techniques use a central base station, which introduces several difficulties into the system due to the network's reliance on a single point, while other ways generate more overhead while jeopardising network lifetime. In this research, an intelligent double hashing-based clone node identification scheme was used, which reduces communication and memory costs while performing the clone detection procedure. The approach works in two stages: in the first, the network is deployed using an intelligent double hashing procedure to avoid any network collisions and then in the second, the clone node identification procedure searches for any clone node in the network. This first phase verifies the node prior to network deployment, and then, whenever a node wants to interact, it executes the second level of authentication. End-to-end delay, which is bound to increase owing to the injection of clone nodes, and packet loss, which is reduced by the double hashing technique, were used to evaluate the performance of the aforementioned approach.

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Section: Related Workmentioning

confidence: 99%

Section: Energy Consumptionmentioning

confidence: 99%

Intelligent Multilevel Node Authentication in Mobile Computing Using Clone Node

Malhotra¹,

Bala²

2022

Computers, Materials &Amp; Continua

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“…A novel distributed clone detection protocol was designed in [18] with lesser resource utilization. The designed protocol increases the detection probability, but the higher packet delivery ratio was not achieved.…”

Section: Related Workmentioning

confidence: 99%

Kriging Regressive Pseudo Randomized Lamport Certificateless Signcryption based Replication Attack Detection for Secure Routing in WSN

D.Sudhakar¹

2021

TURCOMAT

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A Wireless Sensor Network (WSN) includes small, low-cost, and resource-constrained sensor nodes to perform monitoring. Each node is free to move and susceptible to various attacks. Therefore, WSNs have huge attention to communication security. Identifying and monitoring attack node is complex in distributed network and creates node replication attacks in WSN. In order to improve secure routing, a novel technique called Kriging Regressive Attack Detection based Pseudo Randomized Lamport Certificateless Signcryptive Secure Routing (KRAD-PRLCSSR) is proposed. KRAD-PRLCSSR enhances the secure routing by detecting the replication attack in WSN. Initially, the neighbor discovery is performed using the Kriging Regression function. Energy of every sensor node is calculated and validates with threshold value. Based on estimated results, normal node or replica node is identified. Then the normal node is chosen as neighboring node. After that, secure transmission is performed using Pseudo Randomized Lamport one-time Generative Certificateless Signcryption. By applying the signcryption technique, Pseudo Randomized private and public keys are generated for each sensor node. After the key generation, the source node performs the encryption as well as a digital signature. The encrypted data and signature are sent to receiver. Finally, signature is verified at the receiver side to decrypt the data. This helps to increase the security of routing in WSN. The simulation analysis of KRAD-PRLCSSR technique is performed with the different metrics.

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“…This method has high detection accuracy but it restricts the memory for resources. Zhihua Zhang, ShoushanLuo, Hongliang Zhu, Yang Xin [7] used witness based location dependent algorithm and are similar to LSM, RED, LSCD, protocols. It has a higher detection probability equal to 1.…”

Section: Related Workmentioning

confidence: 99%

A Detailed Discussion on Node Replication Attacks in Static WSN

Usha¹

2019

IJRASET

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Wireless sensor nodes gather sensory information from connected nodes that are processed to get relevant results are prone to clone node attacks such as wormhole, sinkhole, eavesdropping and DOS attack where several measures like SET, location aided, witness based detection have been brought to detect them. Clone node attack is one in which the attacker fetch a node from a network and makes a replica to take control over the network. If the attack is not detected then the replica consumes the resource and makes the network vulnerable to large internal attacks. In this literature abundant number of schemes in proposed systems is provided in general that achieves good communication performance, high detection probability, and energy efficiency. But it fails to provide security, effective cost, efficient storage, and accuracy. I.

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A Clone Detection Algorithm with Low Resource Expenditure for Wireless Sensor Networks

Cited by 5 publications

References 17 publications

Intelligent Multilevel Node Authentication in Mobile Computing Using Clone Node

Intelligent Multilevel Node Authentication in Mobile Computing Using Clone Node

Kriging Regressive Pseudo Randomized Lamport Certificateless Signcryption based Replication Attack Detection for Secure Routing in WSN

A Detailed Discussion on Node Replication Attacks in Static WSN

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