AEF: Adaptive En-Route Filtering to Extend Network Lifetime in Wireless Sensor Networks

Shahzad, Muhammad; Islam, S. M. Riazul; Kwak, Kyung Sup; Nkenyereye, Lewis

doi:10.3390/s19184036

Cited by 9 publications

(4 citation statements)

References 43 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

Self Cite

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

Self Cite

View full text Add to dashboard Cite

show abstract

“…Source has to know the routes and the authentication keys of all the nodes, and this makes the system weak. Adaptive En-Route Filtering to Extend Network Lifetime in Wireless Sensor Networks (AEF) is an energy-aware filtering scheme based on a fitness function [30]. It focuses mainly on energy savings with a minimal number of nodes in a cluster.…”

Section: Related Workmentioning

confidence: 99%

“…Hence, the success probability (P FC ) of injecting false data through forwarding cluster is represented as in equation (29). Probability (FP FC ) of filtering false data through en-routers is stated as in equation (30).…”

Section: Performance Evaluationmentioning

confidence: 99%

Rank-Based Report Filtering Scheme (RRFS) for Verifying Phoney Reports in Wireless Sensor Networks

Santhosh

Yogesh

2020

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

Wireless sensor networks (WSNs) are open to false data injection attack when they are deployed in hostile scenarios. Attackers can easily deceive the sink by compromising sensing nodes or by injecting phoney data into the network. Such attacks can deplete the energy resources of the network by providing wrong information which in turn can affect the proper network functioning or sometimes can shut the network from further functioning. The existing schemes that deal with this problem focus on only a few aspects of the false data injection attack. To resolve this problem, we propose a Rank-based Report Filtering Scheme (RRFS), a holistic and group verification scheme for the identification of compromised nodes and the filtering of false data injected into the network. The proposed scheme verifies report among clusters, en-routers, and sink. Hence, the RRFS, a holistic scheme that is composed of three-tier verifications, successfully rejects the false data before the attackers falsify the whole environment, and this makes the system unique. Reliability Index (RI) is calculated by the nodes for fellow cluster members, and the cluster head (CH) provides the score for a node based on its RI. This, in turn, strengthens the scheme by assisting the en-routers to detect the compromised nodes. The RRFS scheme has been verified and validated by extensive simulation and meticulous performance evaluation of filtering efficiency and energy consumption against various schemes. The scheme gives high filtering efficiency against the multiple compromised nodes and also improves the network’s lifespan. The sustainability of RRFS against numerous attacks that are launched in the sensor environment is thoroughly investigated.

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

AEF: Adaptive En-Route Filtering to Extend Network Lifetime in Wireless Sensor Networks

Cited by 9 publications

References 43 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

Rank-Based Report Filtering Scheme (RRFS) for Verifying Phoney Reports in Wireless Sensor Networks

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

Contact Info

Product

Resources

About