An efficient secure key establishment method in cluster-based sensor network

Abstract

The main issue for the security of wireless sensor networks (WSNs) is how to allow sensor nodes (SNs) to establish and share cryptographic keys in an energy-efficient, storage-efficient, and authentic manner for their secure data transmission. Furthermost recent studies carried out in this direction is concerned with homogeneous networks in which all sensor has identical characteristics and key administration mechanisms. Although Cluster-based sensor networks have demonstrated better achievements and performance as compared to homogeneous networks because of the several benefits of clustering. This inspired us to propose a secure key-establishment method for cluster-based sensor networks based on symmetric-key cryptography. Since symmetric key cryptography has small energy consumption, they are a great choice to prefer for securing the networks. Even though symmetric key cryptography has high storage needs, this deficiency can be reduced by using suitable methods-the evaluation of the proposed work that the storage needs are reduced along with reduced energy consumption. The work offers a favorable level of security against various intruders and possible security threats and is additionally scalable than the state-of-the-art techniques.

Data transmission reduction techniques for improving network lifetime in wireless sensor networks: An up‐to‐date survey from 2017 to 2022

“…In 2018, Al-Qurabat et al 58 presented an Adaptive-Distributed Data-Collection (EADiDaC) to resolve the issues of a continuous gathering of huge amounts of redundant sensed measurements. EADiDaC works in cycles and each cycle has four stages: (1) for sampling rate adaptation. This model allows each SN to eliminate the redundant data transmission and also adapts the sampling rate depending on the environmental situations, thus it conserves energy and prolongs network lifetime.…”

“…This work finds correlation features between the data attribute to build a bidirectional LSTM-based data prediction. MNMF considers three factors: (1) the temporal correlation between SN data and past data; (2) the spatial correlation of SN data with other SNs; and (3) the low data quality due to transmission error. MNMF reduces the energy consumption of SNs and extends the WSN lifespan with high prediction accuracy and acceptable bias.…”

“…Wireless sensor networks (WSNs) have been thoughtful as a technology with the possibility to revolutionize the world in which we live. They are widely used in extreme environments such as livestock monitoring, crop survey, wildfire mapping, road patrol, pipeline security, home security, and antipiracy 1 and for monitoring large‐scale applications aerial, underground, terrestrial, and underwater surveillance, as well as multimedia 2 . Other environmental monitoring applications include military service, telecommunication, 3 earthquakes, volcanoes, glaciers, crop monitoring, industry, surveillance, environmental issues, and healthcare.…”

Efficient Key Management Mechanism with Trusted Gateways for Wireless Mesh Networks

“…The implementation of the gateway-level trust has been discussed in Section 3.2. These nodes use the WMN's authentication and deauthentication algorithms that have been discussed in Section 3.3 to ensure that mesh routers can connect securely to the network [26,27].…”

“…In Figures 6(c Figures 6 and 7 depict the probability of mesh router message reachabilities for the proposed DAPM, where the existing schemes are configured with the number of group head values of 5 and 10. Once comparing N G values of 5 and 10, the proposed system gives better performance for authentication and deauthentication policies [25][26][27]. In order to authenticate mesh router in DSA-Mesh, the mesh router message must be received by a minimum of ðN G /2Þ + 1 group heads.…”