A Secure LEACH-PRO Protocol Based on Blockchain

Aljumaie, Ghada Sultan; Alhakami, Wajdi

doi:10.3390/s22218431

Cited by 7 publications

(4 citation statements)

References 30 publications

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“…To ensure the security of patients data this model incorporates clouds based on technology and transfer learning trained models. In their study, Aljumaie et. al., 2022 propose a version of the LEACH PRO protocol that incorporates security techniques to safeguard Wireless Sensor Networks (WSNs) (Aljumaie & Alhakami, 2022).…”

Section: Literature Reviewmentioning

confidence: 91%

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Blockchain Security-Efficiency Analysis based on DEA-SBM Model

VO,

WANG,

YANG

et al. 2023

EPSTEM

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It is estimated that by 2023 the security market will reach a value of $1.4 billion. This growth is primarily driven by the increasing use of technology in sectors like finance, healthcare and logistics. As more companies adopt technology there is a growing need to protect their data from hacking and other malicious activities. The security of the network plays a role in ensuring the implementation and adoption of technology. Given the rise in cyberattacks and data breaches it is expected that the importance of security will continue to grow in the coming years. In this study we will explore some companies that specialize in providing security solutions. Our analysis will be based on three factors and two desired outcomes. The selected companies include Hacken, Quantstamp, OpenZeppelin, Trail of Bits, ConsenSys, Certik, LeastAuthority, PWC Switzerland, Slowmist and Runtime Verification. The purpose of this research paper is to assess the effectiveness of the security industry for decision makers, experts and government entities. By gaining insights into this sector and enhancing network security measures for implementations, across industries.

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Section: Literature Reviewmentioning

confidence: 91%

“…In their study, Aljumaie et. al., 2022 propose a version of the LEACH PRO protocol that incorporates security techniques to safeguard Wireless Sensor Networks (WSNs) (Aljumaie & Alhakami, 2022). Zhao et.…”

Section: Literature Reviewmentioning

confidence: 91%

Blockchain Security-Efficiency Analysis based on DEA-SBM Model

VO,

WANG,

YANG

et al. 2023

EPSTEM

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“…This survey highlights the limitations of existing security protocols in addressing industrial WSNs' speci c security requirements [14], emphasizing the need for tailored security solutions for industrial environments.…”

Section: Literatures Reviewmentioning

confidence: 99%

A Robust Secure Communication Protocol for Wireless Sensor Networks in Industrial Environments

Amara,

Shoaib,

Junaid

et al. 2023

Preprint

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Wireless Sensor Networks (WSNs) have become a popular solution for monitoring and controlling industrial processes. However, these networks are vulnerable to security threats, such as eavesdropping, data tampering, node compromise, and denial of service attacks. To address these challenges, we propose a Robust Secure Communication (RISC) protocol that provides secure and reliable communication for industrial WSNs. In this article, we present the results of our experimental simulations and sensitivity analysis of the RISC protocol, which demonstrate its effectiveness in terms of performance and security. We also compare the RISC protocol with other state-of-the-art security protocols and discuss the strengths and limitations of each approach. Our findings highlight the robustness of the RISC protocol and its effectiveness in securing industrial WSNs against different types of security threats.

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“…The Low Energy Adaptive Clustering Hierarchy (LEACH) protocol is a well-known clustering and hierarchical approach [9][10][11]. Numerous works aimed at improving the performance of the LEACH algorithm have been published [9,[12][13][14][15][16]. Artificial neural networks (ANNs) are used in wireless sensor networks to address problems such as clustering and classification, with the aim of reducing energy consumption [17][18][19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

ANN Based Clusterhead Selection Process in WSN

GANGAL,

SESLI,

HACIOGLU

2024

Preprint

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Wireless sensor networks often face a significant challenge due to their limited energy capacity. To address this challenge, numerous studies are currently underway to explore innovative ways to optimize energy usage. This study proposes an energy-efficient cluster head selection method that is supported by artificial neural networks for cluster-based sensor networks, thereby enhancing their energy efficiency. The neural network is placed in each sensor node. The nodes decide to be the cluster head according to the threshold they set using the ANN, without the need for centralized control. According to the simulation studies conducted, the ANN trained with 5-5-5 neurons survived for 3497 rounds and successfully transmitted 96757 packets to the sink. In contrast, the LEACH algorithm could only survive for 1773 rounds and transmitted 61766 packets to the sink under the same conditions. The study confidently concluded that there was a significant and noteworthy improvement in both the network lifetime and the number of packets sent to the base station. On the other hand, it was also observed that the proposed method showed a notable improvement when compared with similar recent studies conducted with the same parameters by a factor ranging from 3.63 to 6.26.

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A Secure LEACH-PRO Protocol Based on Blockchain

Cited by 7 publications

References 30 publications

Blockchain Security-Efficiency Analysis based on DEA-SBM Model

Blockchain Security-Efficiency Analysis based on DEA-SBM Model

A Robust Secure Communication Protocol for Wireless Sensor Networks in Industrial Environments

ANN Based Clusterhead Selection Process in WSN

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