Blockchain Based Secure Routing and Trust Management in Wireless Sensor Networks

Awan, Saba; Javaid, Nadeem; Ullah, Sameeh; Khan, Asad; Qamar, Ali Mustafa; Choi, Jin-Ghoo

doi:10.3390/s22020411

Cited by 38 publications

(25 citation statements)

References 47 publications

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“…Registration phases are utilized to identify sensor nodes, aggregation nodes, and base stations using smart contact of the public blockchain [59]. The intelligent communications verify the existence of the aggregation node validated by its MAC address and its identity checked by the base station.…”

Section: Simulation and Results Discussionmentioning

confidence: 99%

Localization and Detection of Multiple Attacks in Wireless Sensor Networks Using Artificial Neural Network

Gebremariam

Panda

Indu

2023

Wireless Communications and Mobile Computing

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Security enhancement in wireless sensor networks (WSNs) is significant in different applications. The advancement of routing attack localization is a crucial security research scenario. Various routing attacks degrade the network performance by injecting malicious nodes into wireless sensor networks. Sybil attacks are the most prominent ones generating false nodes similar to the station node. This paper proposed detection and localization against multiple attacks using security localization based on an optimized multilayer perceptron artificial neural network (MLPANN). The proposed scheme has two major part localization techniques and machine learning techniques for detection and localization WSN DoS attacks. The proposed system is implemented using MATLAB simulation and processed with the IBM SPSS toolbox and Python. The dataset is classified into training and testing using the multilayer perceptron artificial neural network to detect ten classes of attacks, including denial-of-service (DoS) attacks. Using the UNSW-NB, WSN-DS, NSL-KDD, and CICIDS2018 benchmark datasets, the results reveal that the suggested system improved with an average detection accuracy of 100%, 99.65%, 98.95%, and 99.83% for various DoS attacks. In terms of localization precision, recall, accuracy, and f-score, the suggested system outperforms state-of-the-art alternatives. Finally, simulations are done to assess how well the suggested method for detecting and localizing harmful nodes performs in terms of security. This method provides a close approximation of the unknown node position with low localization error. The simulation findings show that the proposed system is effective for the detection and secure localization of malicious attacks for scalable and hierarchically distributed wireless sensor networks. This achieved a maximum localization error of 0.49% and average localization accuracy of 99.51% using a secure and scalable design and planning approach.

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Section: Simulation and Results Discussionmentioning

confidence: 99%

Localization and Detection of Multiple Attacks in Wireless Sensor Networks Using Artificial Neural Network

Gebremariam

Panda

Indu

2023

Wireless Communications and Mobile Computing

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“…Awan et al [ 34 ] proposed Blockchain-Assisted-Secure-routing (BASR) mechanisms for WSNs. In this work, WSN participants were categorized as data-transmitting nodes and data aggregator nodes.…”

Section: Methodsmentioning

confidence: 99%

Interleaved Honeypot-Framing Model with Secure MAC Policies for Wireless Sensor Networks

Rajasoundaran

Maheswar

Muthuramalingam

et al. 2022

Sensors

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The Wireless Medium Access Control (WMAC) protocol functions by handling various data frames in order to forward them to neighbor sensor nodes. Under this circumstance, WMAC policies need secure data communication rules and intrusion detection procedures to safeguard the data from attackers. The existing secure Medium Access Control (MAC) policies provide expected and predictable practices against channel attackers. These security policies can be easily breached by any intelligent attacks or malicious actions. The proposed Wireless Interleaved Honeypot-Framing Model (WIHFM) newly implements distributed honeypot-based security mechanisms in each sensor node to act reactively against various attackers. The proposed WIHFM creates an optimal Wireless Sensor Network (WSN) channel model, Wireless Interleaved Honeypot Frames (WIHFs), secure hash-based random frame-interleaving principles, node-centric honeypot engines, and channel-covering techniques. Compared to various existing MAC security policies, the proposed model transforms unpredictable IHFs into legitimate frame sequences against channel attackers. Additionally, introducing WIHFs is a new-fangled approach for distributed WSNs. The successful development of the proposed WIHFM ensures resilient security standards and neighbor-based intrusion alert procedures for protecting MAC frames. Particularly, the proposed wireless honeypot methodology creates a novel idea of using honeypot frame traps against open wireless channel attacks. The development of a novel wireless honeypot traps deals with various challenges such as distributed honeypot management principles (node-centric honeypot, secretly interleaved-framing principles, and interleaving/de-interleaving procedures), dynamic network backbone management principles (On Demand Acyclic Connectivity model), and distributed attack isolation policies. This effort provides an effective wireless attack-trapping solution in dynamic WSNs. The simulation results show the advantage of the proposed WIHFM over the existing techniques such as Secure Zebra MAC (SZ-MAC), Blockchain-Assisted Secure-Routing Mechanism (BASR), and the Trust-Based Node Evaluation (TBNE) procedure. The experimental section confirms the proposed model attains a 10% to 14% superior performance compared to the existing techniques.

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“…The authors of [28] have proposed an encryption and trust evaluation model based on a blockchain in which the identities of the Aggregator Nodes (ANs) and Sensor Nodes (SNs) are stored. The authentication of ANs and SNs is performed in public and private blockchains.…”

Section: Related Workmentioning

confidence: 99%

Utilising Acknowledge for the Trust in Wireless Sensor Networks

et al. 2022

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Wireless Sensor Networks (WSNs) are emerging networks that are being utilized in a variety of applications, such as remote sensing images, military, healthcare, and traffic monitoring. Those critical applications require different levels of security; however, due to the limitation of the sensor networks, security is a challenge where traditional algorithms cannot be used. In addition, sensor networks are considered as the core of the Internet of Things (IoT) and smart cities, where security became one of the most significant problems with IoT and smart cities applications. Therefore, this paper proposes a novel and light trust algorithm to satisfy the security requirements of WSNs. It considers sensor nodes’ limitations and cross-layer information for efficient secure routing in WSNs. It proposes a Tow-ACKs Trust (TAT) Routing protocol for secure routing in WSNs. TAT computes the trust values based on direct and indirect observation of the nodes. TAT uses the first-hand and second-hand information from the Data Link and the Transmission Control Protocol layers to modify the trust’s value. The suggested TATs’ protocols performance is compared to BTRM and Peertrust models in terms of malicious detection ratio, accuracy, average path length, and average energy consumption. The proposed algorithm is compared to BTRM and Peertrust models, the most recent algorithms that proved their efficiency in WSNs. The simulation results indicate that TAT is scalable and provides excellent performance over both BTRM and Peertrust models, even when the number of malicious nodes is high.

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Blockchain Based Secure Routing and Trust Management in Wireless Sensor Networks

Cited by 38 publications

References 47 publications

Localization and Detection of Multiple Attacks in Wireless Sensor Networks Using Artificial Neural Network

Localization and Detection of Multiple Attacks in Wireless Sensor Networks Using Artificial Neural Network

Interleaved Honeypot-Framing Model with Secure MAC Policies for Wireless Sensor Networks

Utilising Acknowledge for the Trust in Wireless Sensor Networks

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