A survey of Sybil attack countermeasures in IoT-based wireless sensor networks

Arshad, Akashah; Hanapi, Zurina Mohd; Subramaniam, Shamala; Latip, Rohaya

doi:10.7717/peerj-cs.673

Cited by 27 publications

(12 citation statements)

References 110 publications

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“…There are quite a number of published articles that outline different Sybil attack detection methods that are applicable to slightly different IoT domains; several recent survey papers summarize these into their associated categories. Recent surveys on Sybil attack detection in wireless ad hoc networks and wireless sensor networks can be found in Arshad et al [12], Vasudeva and Sood [18], and Singh [19]. There are also several recent survey papers on Sybil attack detection in VANETs, including Shobana and Arockia [20], Zhang et al [21], Velayudhan and Anitha [22], and Hammi et al [23].…”

Section: B Sybil Attack Detection In Ioftmentioning

confidence: 99%

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Sybil Attack Detection in Internet of Flying Things-IoFT: A Machine Learning Approach

Chulerttiyawong

Jamalipour

2023

IEEE Internet Things J.

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Sybil attack refers to the situation when a malicious node falsely claims to have numerous identities and is known to be one of the security threats to the Internet of Things (IoT). Due to recent increase usage of unmanned aerial vehicles (UAVs) in various applications, Sybil attack has been identified as a threat to the flying ad hoc network (FANET) paradigm and its integration with the IoT to form the Internet of Flying Things (IoFT). In this paper, we propose an intelligent Sybil attack detection approach for FANETs-based IoFT using physical layer characteristics of the radio signals emitted from the UAVs as detected by two ground nodes. A supervised machine learning approach is employed and experimented with several different classifiers available in the Weka workbench platform. The experiment was carried out based on two features of the radio signals, namely, the received signal strength difference (RSSD) and the time difference of arrival (TDoA). Simulation results revealed that the proposed scheme can achieve a high correct classification accuracy of above 91% on average, even for smart malicious nodes with power control capability operating at power levels not directly trained. In addition to its high performance, the proposed scheme is also less susceptible to various attacks commonly carried out on the upper layers, such as data spoofing, due to the use of only intrinsically generated physical layer data. Furthermore, no additional communications overheads of the UAV nodes are required for the functionality of this scheme.

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Section: B Sybil Attack Detection In Ioftmentioning

confidence: 99%

“…Detection refers to the identification of security breach, the identification of attack type, as well as the initiation of relevant mitigation solutions. Finally, mitigation refers to the alleviation of resulting outcomes of the attack [12].…”

Section: Introductionmentioning

confidence: 99%

Sybil Attack Detection in Internet of Flying Things-IoFT: A Machine Learning Approach

Chulerttiyawong

Jamalipour

2023

IEEE Internet Things J.

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“…In Wireless Sensor Network (WSN) , it is important to identify any mobility gaps and implement an efficient model to maintain network quality and lifetime in a disaster/earthquake, battlefield surveillance, and law enforcement situations 1 . Similarly, in the WSN network, Sybil attacks and their types have been discussed along with the countermeasures in such an environment where the node identifiers or the location can be eavesdropped, modified and masqueraded with today's engineering progress 2 . Therefore, to achieve robust cryptography techniques like lattice cryptography, authors surveyed 3 post‐quantum cryptosystems in an Internet of Things (IoT) environment.…”

Section: Introductionmentioning

confidence: 99%

“…Previously, extensive research methods have been discussed, surveyed, and implemented to restrict Man‐In‐The‐Middle (MITM) and Sybil attacks. There are some strategies or combinations of strategies namely, single and hybrid to prevent, detect and mitigate the Sybil attack 2 and the possible challenges and solutions to prevent MITM attack 4 in an IoT environment using quantum‐based lattice key exchange technique. Apart from offering secure data communication, various hidden metrics should also be considered, which may or may not be directly involved in the implementation of a security scheme.…”

Section: Introductionmentioning

confidence: 99%

“…1 Similarly, in the WSN network, Sybil attacks and their types have been discussed along with the countermeasures in such an environment where the node identifiers or the location can be eavesdropped, modified and masqueraded with today's engineering progress. 2 Therefore, to achieve robust cryptography techniques like lattice cryptography, authors surveyed 3 post-quantum cryptosystems in an Internet of Things (IoT) environment. There are many such examples of cyber attacks in 2016, the Mirai Botnet zombie attack infected smart devices running or ARC processors and targeted almost all the digital devices not to cameras, recorders, and network devices, and in 2017, a ransom-ware attack initiated which demanded Bitcoin payment.…”

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confidence: 99%

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Reliable data communication using post‐quantum encryption in Internet of Everything

Balaji

Dhurandher

2022

Int J Communication

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Summary Internet of Everything (IoE) is one of the emerging technologies in the advancement of digital life and innovation. But the major issue that is to be addressed is the security concerns over such an environment, especially in end‐to‐end device communication. The proposed approach primarily focuses on reliable end‐to‐end device communication using post‐quantum location‐aware encryption, aiming to achieve confidentiality and integrity in an Internet of Everything environment. Even though the post‐quantum techniques have shown to be one of the evolving solutions for reliable data communication, but its robustness against the Man‐In‐The‐Middle and Sybil attacks is still a wide‐open subject and undiscovered. Numerous traditional encryption algorithms are now in use, while post‐quantum encryption is being studied and considered as a quantum‐safe substitute. The proposed approach also demonstrates a robust attack model which focuses on communication network threats like namely, Man‐In‐The‐Middle and Sybil attacks intending to evaluate the overall performance of the network by analyzing the performance parameters like, number of nodes in the network, message size, execution time, and memory consumption by the nodes and aiming to achieve an appreciable accuracy in an IoE environment.

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Secure Internet of Thing based data communication in blockchain model using novel teaching‐learning optimized fuzzy approach

Josphineleela¹,

Pellakuri

Thanuja

et al. 2023

Trans Emerging Tel Tech

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The potential uses in the Internet of Things (IoT), blockchain is gaining prominence. It is particularly skillful at storing data in immutable blocks, which is connected to its protected peer‐to‐peer architecture in the face of a growing challenge of transaction authorization in industrial and service‐provider applications. IoT is prolonged to several additional applications as a result of its integration with various technologies, allowing direct engagement with our individual and professional lives. The major aim of this study is to provide the security based IoT data communication in blockchain using novel techniques. The device's security is a significant concern. However, on‐demand security solutions have issues since devices have limited processing and energy resources. IoT devices do not allow for the use of large, costly systems. In order to address these issues, we present a novel optimized fuzzy architecture for a blockchain‐based IoT device data exchange and communication in this research. The TLBO method is used to improve decision‐making capabilities, while the Mamdani fuzzy inference system makes the majority of the decisions. To construct the two input variables (drop ratio and integrated trust level) and reduce the dimensionality of the input information, the TLBO method was used. We examine and illustrate the efficacy of our method with another state‐of‐art method. Based on the experiment, we have obtained 1.8, 2.1, 2.8, 3.2 and 3.8 ms computational time based on the number of users from 2 to 10, respectively. The proposed method attains 96% accuracy and 95.4% F‐score results than other previous methods.

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A survey of Sybil attack countermeasures in IoT-based wireless sensor networks

Cited by 27 publications

References 110 publications

Sybil Attack Detection in Internet of Flying Things-IoFT: A Machine Learning Approach

Sybil Attack Detection in Internet of Flying Things-IoFT: A Machine Learning Approach

Reliable data communication using post‐quantum encryption in Internet of Everything

Secure Internet of Thing based data communication in blockchain model using novel teaching‐learning optimized fuzzy approach

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