BBAP-WSN: A New Blockchain-Based Authentication Protocol for Wireless Sensor Networks

Dener, Murat; Orman, Abdullah

doi:10.3390/app13031526

Cited by 9 publications

(5 citation statements)

References 61 publications

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“…Dener et al 30 proposed a new authentication protocol, for Wireless Sensor Networks (WSNs) that utilizes technology was introduced. The main goal is to enhance data security in environments with resources and potential lack of trust.…”

Section: Related Workmentioning

confidence: 99%

A scalable blockchain based framework for efficient IoT data management using lightweight consensus

Haque,

Shah,

Iqbal

et al. 2024

Sci Rep

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Recent research has focused on applying blockchain technology to solve security-related problems in Internet of Things (IoT) networks. However, the inherent scalability issues of blockchain technology become apparent in the presence of a vast number of IoT devices and the substantial data generated by these networks. Therefore, in this paper, we use a lightweight consensus algorithm to cater to these problems. We propose a scalable blockchain-based framework for managing IoT data, catering to a large number of devices. This framework utilizes the Delegated Proof of Stake (DPoS) consensus algorithm to ensure enhanced performance and efficiency in resource-constrained IoT networks. DPoS being a lightweight consensus algorithm leverages a selected number of elected delegates to validate and confirm transactions, thus mitigating the performance and efficiency degradation in the blockchain-based IoT networks. In this paper, we implemented an Interplanetary File System (IPFS) for distributed storage, and Docker to evaluate the network performance in terms of throughput, latency, and resource utilization. We divided our analysis into four parts: Latency, throughput, resource utilization, and file upload time and speed in distributed storage evaluation. Our empirical findings demonstrate that our framework exhibits low latency, measuring less than 0.976 ms. The proposed technique outperforms Proof of Stake (PoS), representing a state-of-the-art consensus technique. We also demonstrate that the proposed approach is useful in IoT applications where low latency or resource efficiency is required.

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Section: Related Workmentioning

confidence: 99%

A scalable blockchain based framework for efficient IoT data management using lightweight consensus

Haque,

Shah,

Iqbal

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…In [34], a novel blockchain-based authentication protocol for Wireless Sensor Networks (WSNs) is introduced. The aim is to enhance the security of data obtained in resource constrained and potentially untrusted environments.…”

Section: A Blockchain Based Iot Data Managementmentioning

confidence: 99%

A Scalable Blockchain-based Framework for Efficient IoT Data Management Using Lightweight Consensus

Haque,

Shah,

Iqbal

et al. 2024

Preprint

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Recent research has focused on applying blockchain technology to solve security-related problems in Internet of Things (IoT) networks. However, the inherent scalability issues of blockchain technology become apparent in the presence of a vast number of IoT devices and the substantial data generated by these networks. Therefore, in this paper, we use a lightweight consensus algorithm to cater to these problems. We propose a scalable blockchain-based framework for managing IoT data, catering to a large number of devices. This framework utilizes the Delegated Proof of Stake (DPoS) consensus algorithm to ensure enhanced performance and efficiency in resource-constrained IoT networks. DPoS being a lightweight consensus algorithm leverages a selected number of elected delegates to validate and confirm transactions, thus mitigating the performance and efficiency degradation in the blockchain-based IoT networks. In this paper, we implemented an Interplanetary File System (IPFS) for distributed storage, and Docker to evaluate the network’s performance in terms of throughput, latency, and resource utilization. We divided our analysis into four parts: Latency, throughput, resource utilization, and file upload time and speed in distributed storage evaluation. Our empirical findings demonstrate that our framework exhibits low latency, measuring less than 0.976 milliseconds. The proposed technique outperforms Proof of Stake (PoS), representing a state-of-the-art consensus technique. We also demonstrate that the proposed approach is useful in IoT applications where low latency or resource efficiency is required.

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“…They employed an artificial neural network (ANN) on this dataset, which resulted in enhanced accuracy in the detection and classification of DoS attacks. Subsequently, in 2023, Dener et al [22] introduced a novel dataset, WSN-BFSF, specifically designed to detect DoS attacks in WSNs. Their investigation involved the evaluation of four ML and eight deep-learning models, yielding notable outcomes.…”

Section: Wsn Intrusion Detectionmentioning

confidence: 99%

Enhancing Intrusion Detection in Wireless Sensor Networks Using a GSWO-CatBoost Approach

Nguyen,

Vo,

Yoo

2024

Sensors

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Intrusion detection systems (IDSs) in wireless sensor networks (WSNs) rely heavily on effective feature selection (FS) for enhanced efficacy. This study proposes a novel approach called Genetic Sacrificial Whale Optimization (GSWO) to address the limitations of conventional methods. GSWO combines a genetic algorithm (GA) and whale optimization algorithms (WOA) modified by applying a new three-population division strategy with a proposed conditional inherited choice (CIC) to overcome premature convergence in WOA. The proposed approach achieves a balance between exploration and exploitation and enhances global search abilities. Additionally, the CatBoost model is employed for classification, effectively handling categorical data with complex patterns. A new technique for fine-tuning CatBoost’s hyperparameters is introduced, using effective quantization and the GSWO strategy. Extensive experimentation on various datasets demonstrates the superiority of GSWO-CatBoost, achieving higher accuracy rates on the WSN-DS, WSNBFSF, NSL-KDD, and CICIDS2017 datasets than the existing approaches. The comprehensive evaluations highlight the real-time applicability and accuracy of the proposed method across diverse data sources, including specialized WSN datasets and established benchmarks. Specifically, our GSWO-CatBoost method has an inference time nearly 100 times faster than deep learning methods while achieving high accuracy rates of 99.65%, 99.99%, 99.76%, and 99.74% for WSN-DS, WSNBFSF, NSL-KDD, and CICIDS2017, respectively.

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BBAP-WSN: A New Blockchain-Based Authentication Protocol for Wireless Sensor Networks

Cited by 9 publications

References 61 publications

A scalable blockchain based framework for efficient IoT data management using lightweight consensus

A scalable blockchain based framework for efficient IoT data management using lightweight consensus

A Scalable Blockchain-based Framework for Efficient IoT Data Management Using Lightweight Consensus

Enhancing Intrusion Detection in Wireless Sensor Networks Using a GSWO-CatBoost Approach

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