Secure Internet of Things based hybrid optimization techniques for optimal centroid routing protocol in wireless sensor network

Mudasser, Abdul Wasay; Gafoor, Shah Aqueel Ahmed Abdul

doi:10.1002/cpe.7585

Cited by 3 publications

(1 citation statement)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A wireless sensor network (WSN) is a collection of wireless sensors which operates within a shared range and transmits messages in the form of a signal from one device to another. [2][3][4] In particular, the WSN will be served as a sensing module for many IoT applications where the IoT-enabled WSN (IWSNs) are utilized to monitor the physical environments. The different subsystems that make up a sensor include CPUs, memory, power supplies, sensing sub-systems, and actuators.…”

Section: Introductionmentioning

confidence: 99%

An artificial intelligence approach for energy‐aware intrusion detection and secure routing in internet of things‐enabled wireless sensor networks

Aruchamy,

Gnanaselvi,

Sowndarya

et al. 2023

Concurrency and Computation

View full text Add to dashboard Cite

SummaryIn today's world, the Internet of things (IoT) and wireless sensor networks (WSNs) have been integrated into various applications to support reliable communication systems. The IoT nodes collect the sensed data with the aid of WSN and transfer them to the cloud environment. Nevertheless, these nodes become vulnerable when Denial of Service attacks occurred in the IoT‐enabled WSN (IWSN). The insecure route also affects the energy efficiency of IWSN. Therefore, robust intrusion detection along with secure routing is necessitated to protect the IWSN from various security threats. In this paper, a novel Artificial Intelligence‐based Energy‐aware Intrusion Detection and Secure Routing model has been proposed to develop a secured IWSN. Initially, the proposed model executes the intrusion detection system to identify the various attacks. Afterward, a game strategy‐based decision mechanism is integrated with the proposed intrusion detection model to decide whether protection is needed or not. In the last phase, an energy‐aware ad‐hoc on‐demand distance vector algorithm has been established to offer secured routing among multiple nodes. The performance results show that the proposed model achieves superior detection accuracy of 95% and reduced energy utilization of 38% as compared with the existing intrusion detection models.

show abstract

Section: Introductionmentioning

confidence: 99%

An artificial intelligence approach for energy‐aware intrusion detection and secure routing in internet of things‐enabled wireless sensor networks

Aruchamy,

Gnanaselvi,

Sowndarya

et al. 2023

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

Energy efficient clustering and sink mobility protocol using Improved Dingo and Boosted Beluga Whale Optimization Algorithm for extending network lifetime in WSNs

Sahayaraj,

Gunasekaran,

Verma

et al. 2024

Sustainable Computing: Informatics and Systems

View full text Add to dashboard Cite

An energy-aware cluster-based routing in the Internet of things using particle swarm optimization algorithm and fuzzy clustering

Lei

2024

J. Eng. Appl. Sci.

View full text Add to dashboard Cite

The effectiveness and longevity of IoT infrastructures heavily depend on the limitations posed by communication, multi-hop data transfers, and the inherent difficulties of wireless links. In dealing with these challenges, routing, and data transmission procedures are critical. Among the fundamental concerns are the attainment of energy efficiency and an ideal distribution of loads among sensing devices, given the restricted energy resources at the disposal of IoT devices. To meet these challenges, the present research suggests a novel hybrid energy-aware IoT routing approach that mixes the Particle Swarm Optimization (PSO) algorithm and fuzzy clustering. The approach begins with a fuzzy clustering algorithm to initially group sensor nodes by their geographical location and assign them to clusters determined by a certain probability. The proposed method includes a fitness function considering energy consumption and distance factors. This feature guides the optimization process and aims to balance energy efficiency and data transmission distance. The hierarchical topology uses the advanced PSO algorithm to identify the cluster head nodes. The MATLAB simulator shows that our method outperforms previous approaches. Various metrics have demonstrated significant improvements over DEEC and LEACH. The method reduces energy consumption by 52% and 16%, improves throughput by 112% and 10%, increases packet delivery rates by 83% and 15%, and extends the network lifespan by 48% and 27%, respectively, compared to DEEC and LEACH approaches.

show abstract

Secure Internet of Things based hybrid optimization techniques for optimal centroid routing protocol in wireless sensor network

Cited by 3 publications

References 32 publications

An artificial intelligence approach for energy‐aware intrusion detection and secure routing in internet of things‐enabled wireless sensor networks

An artificial intelligence approach for energy‐aware intrusion detection and secure routing in internet of things‐enabled wireless sensor networks

Energy efficient clustering and sink mobility protocol using Improved Dingo and Boosted Beluga Whale Optimization Algorithm for extending network lifetime in WSNs

An energy-aware cluster-based routing in the Internet of things using particle swarm optimization algorithm and fuzzy clustering

Contact Info

Product

Resources

About