Trust Based Data Gathering in Wireless Sensor Network

Karthik, N.; Ananthanarayana, V. S.

doi:10.1007/s11277-019-06491-y

Cited by 6 publications

(4 citation statements)

References 24 publications

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“…In [ 28 ], a trust-based data gathering approach is proposed that focuses on collecting data in a sensor-driven environment through data aggregation and reconstruction. The concept of multidimensional trust was introduced, incorporating communication, data, resource, and forwarding trust.…”

Section: Literature Surveymentioning

confidence: 99%

Variable-Length Multiobjective Social Class Optimization for Trust-Aware Data Gathering in Wireless Sensor Networks

Saad

Jaafar

Chellappan

2023

Sensors

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Data gathering in wireless sensor networks (WSNs) is vital for deploying and enabling WSNs with the Internet of Things (IoTs). In various applications, the network is deployed in a large-scale area, which affects the efficiency of the data collection, and the network is subject to multiple attacks that impact the reliability of the collected data. Hence, data collection should consider trust in sources and routing nodes. This makes trust an additional optimization objective of the data gathering in addition to energy consumption, traveling time, and cost. Joint optimization of the goals requires conducting multiobjective optimization. This article proposes a modified social class multiobjective particle swarm optimization (SC-MOPSO) method. The modified SC-MOPSO method is featured by application-dependent operators named interclass operators. In addition, it includes solution generation, adding and deleting rendezvous points, and moving to the upper and lower class. Considering that SC-MOPSO provides a set of nondominated solutions as a Pareto front, we employed one of the multicriteria decision-making (MCDM) methods, i.e., simple additive sum (SAW), for selecting one of the solutions from the Pareto front. The results show that both SC-MOPSO and SAW are superior in terms of domination. The set coverage of SC-MOPSO is 0.06 dominant over NSGA-II compared with only a mastery of 0.04 of NSGA-II over SC-MOPSO. At the same time, it showed competitive performance with NSGA-III.

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Section: Literature Surveymentioning

confidence: 99%

Variable-Length Multiobjective Social Class Optimization for Trust-Aware Data Gathering in Wireless Sensor Networks

Saad

Jaafar

Chellappan

2023

Sensors

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“…The presence of a dispersed network or cloud highlights the importance of trust in providing security, privacy, and dependable communication in the network [43].…”

Section: Related Workmentioning

confidence: 99%

Swarm Intelligence-Optimized Energy Management for Prolonging the Lifetime of Wireless Sensor Networks

Amuthavalli L

2023

IJRITCC

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Recent technological and industrial progress has enabled the development of small, high-performing, energy-saving, affordable sensor nodes that possess the potential to adapt, be self-aware, and self-organize. These nodes are designed for versatile communications applications. Sensor networks for sustainable development focus on the ways in which sensor network technology can enhance social development and improve living standards without causing harm to the environment or depleting natural resources. Wireless sensor networks (WSNs) offer undeniable benefits in various fields, including the military, healthcare, traffic monitoring, and remote image sensing. Given the constraints of sensor networks, varying degrees of security are necessary for these critical applications, posing difficulties in the implementation of conventional algorithms. The issue of security has emerged as a primary concern in the context of IoT and smart city applications. Sensor networks are often regarded as the fundamental building blocks of IoTs and smart cities. The WSN encompasses a routing algorithm, network strength, packet loss, energy loss, and various other intricate considerations. The WSN also addresses intricate matters such as energy usage, a proficient approach for picking cluster heads, and various other concerns. The recent growth of Wireless Sensor Networks (WSNs) has made it increasingly difficult to ensure the trustworthiness and reliability of data due to the distinct features and limitations of nodes. Hostile nodes can easily damage the integrity of the network by inserting fake and malicious data, as well as launching internal attacks. Trust-based security is employed to detect and identify rogue nodes, providing a robust and adaptable protection mechanism. Trust evaluation models are crucial security-enhancement mechanisms that enhance the reliability and collaboration of sensor nodes in wireless sensor networks. This study recommends the use of DFA UTrust, a unique trust technique, to effectively satisfy the security requirements of WSNs.

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“…Although AES has been implemented quickly, however, it is still very complicated and has big codes that do not comply with the needs [19]. In [20], it is mentioned that AES is utilized as validation component in RFID-based frameworks. The AES is used in the application layer as an integrated COAP system.…”

Section: Related Workmentioning

confidence: 99%

LLSFIoT: Lightweight Logical Security Framework for Internet of Things

Batra

Hamatta

Malik

et al. 2021

Wireless Communications and Mobile Computing

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Current research in Internet of Things (IoT) is focused on the security enhancements to every communicated message in the network. Keeping this thought in mind, researcher in this work emphasizes on a security oriented cryptographic solution. Commonly used security cryptographic solutions are heavy in nature considering their key size, operations, and mechanism they follow to secure a message. This work first determines the benefit of applying lightweight security cryptographic solutions in IoT. The existing lightweight counterparts are still vulnerable to attacks and also consume calculative more power. Therefore, this research work proposes a new hybrid lightweight logical security framework for offering security in IoT (LLSFIoT). The operations, key size, and mechanism used in the proposed framework make its lightweight. The proposed framework is divided into three phases: registration, authentication, and light data security (LDS). LDS offers security by using unique keys at each round bearing small size. Key generation mechanism used is comparatively fast making the compromise of keys as a difficult task. These steps followed in the proposed algorithm design make it lightweight and a better solution for IoT-based networks as compared to the existing solutions that are relatively heavy weight in nature.

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Trust Based Data Gathering in Wireless Sensor Network

Cited by 6 publications

References 24 publications

Variable-Length Multiobjective Social Class Optimization for Trust-Aware Data Gathering in Wireless Sensor Networks

Variable-Length Multiobjective Social Class Optimization for Trust-Aware Data Gathering in Wireless Sensor Networks

Swarm Intelligence-Optimized Energy Management for Prolonging the Lifetime of Wireless Sensor Networks

LLSFIoT: Lightweight Logical Security Framework for Internet of Things

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