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用于高效安全无线传感器网络的基于加密的经济高效自主路由协议

Cost-Effective Encryption-Based Autonomous Routing Protocol for Efficient and Secure Wireless Sensor Networks.

作者信息

Saleem Kashif, Derhab Abdelouahid, Orgun Mehmet A, Al-Muhtadi Jalal, Rodrigues Joel J P C, Khalil Mohammed Sayim, Ali Ahmed Adel

机构信息

Center of Excellence in Information Assurance (CoEIA), King Saud University, Riyadh 12372, Saudi Arabia.

Intelligent Systems Group (ISG), Department of Computing, Macquarie University, Sydney, NSW 2109, Australia.

出版信息

Sensors (Basel). 2016 Mar 31;16(4):460. doi: 10.3390/s16040460.

DOI:10.3390/s16040460
PMID:27043572
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4850974/
Abstract

The deployment of intelligent remote surveillance systems depends on wireless sensor networks (WSNs) composed of various miniature resource-constrained wireless sensor nodes. The development of routing protocols for WSNs is a major challenge because of their severe resource constraints, ad hoc topology and dynamic nature. Among those proposed routing protocols, the biology-inspired self-organized secure autonomous routing protocol (BIOSARP) involves an artificial immune system (AIS) that requires a certain amount of time to build up knowledge of neighboring nodes. The AIS algorithm uses this knowledge to distinguish between self and non-self neighboring nodes. The knowledge-building phase is a critical period in the WSN lifespan and requires active security measures. This paper proposes an enhanced BIOSARP (E-BIOSARP) that incorporates a random key encryption mechanism in a cost-effective manner to provide active security measures in WSNs. A detailed description of E-BIOSARP is presented, followed by an extensive security and performance analysis to demonstrate its efficiency. A scenario with E-BIOSARP is implemented in network simulator 2 (ns-2) and is populated with malicious nodes for analysis. Furthermore, E-BIOSARP is compared with state-of-the-art secure routing protocols in terms of processing time, delivery ratio, energy consumption, and packet overhead. The findings show that the proposed mechanism can efficiently protect WSNs from selective forwarding, brute-force or exhaustive key search, spoofing, eavesdropping, replaying or altering of routing information, cloning, acknowledgment spoofing, HELLO flood attacks, and Sybil attacks.

摘要

智能远程监控系统的部署依赖于由各种资源受限的微型无线传感器节点组成的无线传感器网络(WSN)。由于WSN存在严重的资源限制、自组织拓扑结构和动态特性,其路由协议的开发是一项重大挑战。在那些已提出的路由协议中,受生物学启发的自组织安全自主路由协议(BIOSARP)涉及一种人工免疫系统(AIS),该系统需要一定时间来建立对相邻节点的认知。AIS算法利用这些认知来区分自身与非自身的相邻节点。知识构建阶段是WSN生命周期中的关键时期,需要采取积极的安全措施。本文提出了一种增强型BIOSARP(E - BIOSARP),它以经济高效的方式纳入了随机密钥加密机制,以便在WSN中提供积极的安全措施。文中详细描述了E - BIOSARP,随后进行了广泛的安全和性能分析以证明其效率。在网络模拟器2(ns - 2)中实现了一个使用E - BIOSARP的场景,并引入恶意节点进行分析。此外,还将E - BIOSARP与当前最先进的安全路由协议在处理时间、传输率、能耗和数据包开销方面进行了比较。研究结果表明,所提出的机制能够有效地保护WSN免受选择性转发、暴力或穷举密钥搜索、欺骗、窃听、路由信息的重放或篡改、克隆、确认欺骗、HELLO泛洪攻击和Sybil攻击。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/b0475d4e2dec/sensors-16-00460-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/aabf8f98c177/sensors-16-00460-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/7bf9c1f84328/sensors-16-00460-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/a97fa711d2fc/sensors-16-00460-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/fe9d363e72a7/sensors-16-00460-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/f0bccd4f0d45/sensors-16-00460-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/36cefe97723d/sensors-16-00460-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/31c23777572d/sensors-16-00460-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/8591fc143895/sensors-16-00460-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/8b73c54a562c/sensors-16-00460-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/376b96b446f5/sensors-16-00460-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/b0c558d5bdad/sensors-16-00460-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/340f484317b9/sensors-16-00460-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/b0475d4e2dec/sensors-16-00460-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/aabf8f98c177/sensors-16-00460-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/7bf9c1f84328/sensors-16-00460-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/a97fa711d2fc/sensors-16-00460-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/fe9d363e72a7/sensors-16-00460-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/f0bccd4f0d45/sensors-16-00460-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/36cefe97723d/sensors-16-00460-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/31c23777572d/sensors-16-00460-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/8591fc143895/sensors-16-00460-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/8b73c54a562c/sensors-16-00460-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/376b96b446f5/sensors-16-00460-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/b0c558d5bdad/sensors-16-00460-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/340f484317b9/sensors-16-00460-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/642e/4850974/b0475d4e2dec/sensors-16-00460-g014.jpg

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