A Fuzzy System based Approach to Extend Network Lifetime for En-Route Filtering Schemes in WSNs

Shahzad, Muhammad; Nkenyereye, Lewis; Islam, Saiful

doi:10.1145/3313991.3314004

Cited by 3 publications

(3 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Research works [14][15][16][17] present various attack types and their counter measures in en-route filtering schemes. Some interesting works exist for improving network lifetime [18][19][20][21][22][23][24] and energy efficiency [25][26][27][28][29]. Re-clustering based schemes to increase network lifetime [30][31][32][33][34][35][36] have been found effective in minimizing the hot-spot problem.…”

Section: Literature Reviewmentioning

confidence: 99%

GAFOR: Genetic Algorithm Based Fuzzy Optimized Re-Clustering in Wireless Sensor Networks

et al. 2020

View full text Add to dashboard Cite

In recent years, the deployment of wireless sensor networks has become an imperative requisite for revolutionary areas such as environment monitoring and smart cities. The en-route filtering schemes primarily focus on energy saving by filtering false report injection attacks while network lifetime is usually ignored. These schemes also suffer from fixed path routing and fixed response to these attacks. Furthermore, the hot-spot is considered as one of the most crucial challenges in extending network lifetime. In this paper, we have proposed a genetic algorithm based fuzzy optimized re-clustering scheme to overcome the said limitations and thereby minimize the effect of the hot-spot problem. The fuzzy logic is applied to capture the underlying network conditions. In re-clustering, an important question is when to perform next clustering. To determine the time instant of the next re-clustering (i.e., number of nodes depleted—energy drained to zero), associated fuzzy membership functions are optimized using genetic algorithm. Simulation experiments validate the proposed scheme. It shows network lifetime extension of up to 3.64 fold while preserving detection capacity and energy-efficiency.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

GAFOR: Genetic Algorithm Based Fuzzy Optimized Re-Clustering in Wireless Sensor Networks

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Because of the hardware limits, security methods must be exceedingly efficient. is is no trivial task [4]. Sensor networks' most valuable resource is energy.…”

Section: Introductionmentioning

confidence: 99%

Vampire Attack Mitigation and Network Performance Improvement Using Probabilistic Fuzzy Chain Set with Authentication Routing Protocol and Hybrid Clustering-Based Optimization in Wireless Sensor Network

Alkwai

Aledaily

Almansour

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

The most effective threat for wireless sensor networks (WSN) is Vampire attacks on sensor nodes as they can stretch the network connectivity among them and influence the network’s energy, which can drain the network. Vampire attack has particular malicious nature of sensor nodes in which they can widely exploit features of combined routing protocol. Fuzzy rules and fuzzy sets are highly optimal techniques in mitigating the vampire attacks of the network, which can quantify the uncertain behaviour of sensor nodes. This study aims to propose a novel technique using a probabilistic fuzzy chain set with authentication-based routing protocol and hybrid clustering technique for data optimization of the network. The suggested approach here employs a fuzzy-based chain rule set to combat growing types of vampire assaults using probability formulas. The authentication routing protocol has increased network routing security. The proposed technique (PFCS-ARP_HC) has optimized the energy consumption of network. Simulation for this technique has been carried out using NS2 and experimental results show the performance of the proposed model in terms of throughput of 98%, packet delivery ratio of 89%, energy consumption of 67%, latency of 46% control overhead of 53%, and attack detection ratio of 87.9%.

show abstract

“…In order to resist false data injection attacks and filter out false data reports as early as possible, scholars have proposed a number of en-route filtering strategies, in which the forwarding nodes verify the data reports and discard the false ones. According to the adopted data encryption technology, the existing en-route filtering strategies can be classified into symmetric cryptography-based strategies [5][6][7][8][9][10][11][12][13][14] and asymmetric cryptography-based strategies [15][16][17][18][19][20][21][22]. Among them, the symmetric cryptography-based strategies attract more attention because of their advantages in communication overhead, computation overhead, and storage overhead.…”

Section: Introductionmentioning

confidence: 99%

En-Route Message Authentication Scheme for Filtering False Data in WSNs

Chuanjun

2021

Security and Communication Networks

View full text Add to dashboard Cite

In wireless sensor networks, the adversary can easily control the compromised nodes to inject false data reports. En-route filtering is an effective mechanism to resist such attacks, where the forwarding nodes of the reports can identify and drop the false reports. However, the existing en-route filtering strategies are vulnerable to report disruption attacks and selective forwarding attacks, and the probabilities and efficiencies of en-route filtering false reports are low. To address these problems, a precheck mechanism performed by the CoS (Center-of-Stimulus) node is presented to resist report disruption attacks, a report forwarding strategy with balancing the residual energy of the nodes is designed to resist selective forwarding attacks, and an en-route message authentication scheme (EMAS) based on monitoring and reporting mechanism is proposed to resist false data injection attacks. The theoretical analysis and simulation results show that in most cases, EMAS provides a higher security level and higher en-route filtering probability and efficiency and is very efficient in energy saving.

show abstract

A Fuzzy System based Approach to Extend Network Lifetime for En-Route Filtering Schemes in WSNs

Cited by 3 publications

References 10 publications

GAFOR: Genetic Algorithm Based Fuzzy Optimized Re-Clustering in Wireless Sensor Networks

GAFOR: Genetic Algorithm Based Fuzzy Optimized Re-Clustering in Wireless Sensor Networks

Vampire Attack Mitigation and Network Performance Improvement Using Probabilistic Fuzzy Chain Set with Authentication Routing Protocol and Hybrid Clustering-Based Optimization in Wireless Sensor Network

En-Route Message Authentication Scheme for Filtering False Data in WSNs

Contact Info

Product

Resources

About