Secret Key Management in Wireless Sensor Network Based on Probabilistic Technique

Aniebiet Effiong Bassey, Enyenihi Henry Johnson, Gabriel Etim Umoh
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Abstract

Data confidentiality implies that data access is limited to authorized entities only, thus measured data and transmitted data by wireless sensors require optimum security and privacy. Various techniques have been employed to implement effective security mechanisms for a wireless sensor network. However, the arsenal of these potential solutions is useless, considering the constrained nature of the Wireless Sensor Network (WSN) resources in terms of memory, processing and computational capacity. While considering an effective solution for this situation, care must be taken not to trade the desired solution for other factors. This paper considers the implementation of a probabilistic approach for key management in WSN. In the implementation, all kinds of communication within the wireless sensor nodes are presented by forwarding encrypted keys for mutual authentication. A successful authentication opens a communication channel for the communicating nodes. The encrypted keys are computed by generating a polynomial which constitutes the hashed ID concatenated with the master key and Message Authentication Code (MAC) address of the node. The results presented from the simulation of this model are benchmarked with the Dynamically Generated Polynomial (DGP). The proposed model was simulated using MATLAB tools and the comparison of the results obtained shows that the proposed model outperforms the DGP model by 87%, based on the key metrics which are energy consumption, storage and communication overhead.
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基于概率技术的无线传感器网络密钥管理
数据保密意味着数据访问仅限于授权实体,因此无线传感器测量的数据和传输的数据需要最佳的安全性和隐私性。人们采用了各种技术为无线传感器网络实施有效的安全机制。然而,考虑到无线传感器网络(WSN)资源在内存、处理和计算能力方面的局限性,这些潜在解决方案的武库毫无用处。在考虑针对这种情况的有效解决方案时,必须注意不要以其他因素来换取所需的解决方案。本文考虑在 WSN 中实施一种概率密钥管理方法。在实施过程中,无线传感器节点内部的各种通信都是通过转发加密密钥进行相互验证来实现的。成功的身份验证会为通信节点打开一条通信通道。加密密钥是通过生成一个多项式来计算的,该多项式由节点的哈希 ID、主密钥和消息验证码(MAC)地址构成。该模型的模拟结果以动态生成多项式(DGP)为基准。使用 MATLAB 工具对所提出的模型进行了仿真,结果比较显示,从能耗、存储和通信开销等关键指标来看,所提出的模型比 DGP 模型高出 87%。
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