A multi-level study of information trust models in WSN-assisted IoT

Souissi, Ilhem; Azzouna, Nadia Ben; Saïd, Lamjed Ben

doi:10.1016/j.comnet.2019.01.010

Cited by 47 publications

(22 citation statements)

References 50 publications

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“…A survey on recent advancements in data trust, communication trust in WSN-assisted IoT was designed [5]. However, security for both data and route was not ensured.…”

Section: Related Workmentioning

confidence: 99%

Optimized Load Centroid and Rabin Onion Secured Routing in Wireless Sensor Network for IoT

Mohanraj¹

2020

GJCST

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Advances in wireless communication have geared up extensive insights wherein the sensors can themselves communicate with other sensors that form significant parts of the Internet of Things (IoT). However, the large-scale acceptance of WSN for IoT is still surfacing threats and controversies that apprehend the security aspects. There are a lot of attacks that can manipulate the routein WSN for IoT. In this work, an Optimized Load Centroid and Rabin Onion Routing (OLC-ROR) method are designed to improve the throughput rate with minimum routing overhead and latency. The proposed method is based on a Centroid and Rabin Signature, a Digital Signature technique. First, the optimal route is identified by considering both the load and residual energy using Load Centroid function. Then onion routing is used for selecting secured route amongst the optimality. Besides, the node genuineness is checked by applying the Rabin Signature.

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“…A survey on recent advancements in data trust, communication trust in WSN-assisted IoT was designed [5]. However, security for both data and route was not ensured.…”

Section: Related Workmentioning

confidence: 99%

Optimized Load Centroid and Rabin Onion Secured Routing in Wireless Sensor Network for IoT

Mohanraj¹

2020

GJCST

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“…Multiple information sources such as sensors generate information which is collected by sink node(s), where the information fusion processes take place. These processes may include transformation, reduction, integration, or replacement [8,14,15,16]. Finally, an output is generated that is hopefully more useful than that provided by any individual information source.…”

Section: The Need For Trust-based Information Fusionmentioning

confidence: 99%

“…On the other hand, behavior issues for IoT devices have just recently started to get attention from the research community [1,7,8,9,10,11,12]. Having created a smart environment, the IoT vision is to allow different sensors to disseminate vital data including the human body and environmental measurements.…”

Section: Introductionmentioning

confidence: 99%

“…If these sensors act maliciously, catastrophes may occur in these already complex IoT systems. Furthermore, and since these devices closely affect human life, disastrous consequences are posed by injecting false data [8,12].…”

Section: Introductionmentioning

confidence: 99%

“…Information fusion phases can be applied on sensors-generated information to ensure data reliability [8,14,15,16]. Information fusion techniques can combine data from multiple data sources to increase data reliability.…”

Section: Introductionmentioning

confidence: 99%

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Internet-of-Things and Information Fusion: Trust Perspective Survey

Azzedin

Ghaleb

2019

Sensors

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The advent of Internet-of-Things (IoT) is creating an ecosystem of smart applications and services enabled by a multitude of sensors. The real value of these IoT smart applications comes from analyzing the information provided by these sensors. Information fusion improves information completeness/quality and, hence, enhances estimation about the state of things. Lack of trust and therefore, malicious activities renders the information fusion process and hence, IoT smart applications unreliable. Behavior-related issues associated with the data sources, such as trustworthiness, honesty, and accuracy, must be addressed before fully utilizing these smart applications. In this article, we argue that behavior trust modeling is indispensable to the success of information fusion and, hence, to smart applications. Unfortunately, the area is still in its infancy and needs further research to enhance information fusion. The aim of this article is to raise the awareness and the need of behavior trust modelling and its effect on information fusion. Moreover, this survey describes IoT architectures for modelling trust as well as classification of current IoT trust models. Finally, we discuss future directions towards trustworthy reliable fusion techniques.

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DEICA: A differential evolution‐based improved clustering algorithm for IoT‐based heterogeneous wireless sensor networks

Chaurasiya

Biswas

Nayyar

et al. 2023

Int J Communication

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With the evolution of technology, many modern applications like habitat monitoring, environmental monitoring, disaster prediction and management, and telehealth care have been proposed on wireless sensor networks (WSNs) with Internet of Things (IoT) integration. However, the performance of these networks is restricted because of the various constraints imposed due to the participating sensor nodes, such as nonreplaceable limited power units, constrained computation, and limited storage. Power limitation is the most severe among these restrictions. Hence, the researchers have sought schemes enabling energy-efficient network operations as the most crucial issue. A metaheuristic clustering scheme is proposed here to address this problem, which employs the differential evolution (DE) technique as a tool. The proposed scheme achieves improved network performance via the formulation of loadbalanced clusters, resulting in a more scalable and adaptable network. The proposed scheme considers multiple parameters such as nodes' energy level, degree, proximity, and population for suitable network partitioning. Through various simulation results and experimentation, it establishes its efficacy over state-of-the-art schemes in respect of load-balanced cluster formation, improved network lifetime, network resource utilization, and network throughput. The proposed scheme ensures up to 57.69%, 33.16%, and 57.74% gains in network lifetime, energy utilization, and data packet delivery under varying network configurations. Besides providing the quantitative analysis, a detailed statistical analysis has also been performed that describes the acceptability of the proposed scheme under different network configurations.

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A multi-level study of information trust models in WSN-assisted IoT

Cited by 47 publications

References 50 publications

Optimized Load Centroid and Rabin Onion Secured Routing in Wireless Sensor Network for IoT

Optimized Load Centroid and Rabin Onion Secured Routing in Wireless Sensor Network for IoT

Internet-of-Things and Information Fusion: Trust Perspective Survey

DEICA: A differential evolution‐based improved clustering algorithm for IoT‐based heterogeneous wireless sensor networks

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