TrustSense：一种能量有效的分簇无线传感器网络信任机制
TrustSense: An energy efficient trust scheme for clustered wireless sensor networks
摘要：
由于无线传感器网络的计算资源相对较低，因此设计安全系统是一个挑战。这使得许多基于密码学的传统防御机制无法在此类网络上部署。声誉和异常检测系统已被实现为可行的替代方案，但现有的实现仍然难以在不对能耗产生重大影响的情况下提供有效的安全性。为了解决这种资源消耗和弹性之间的权衡，我们设计了TrustSense，一个信誉管理协议的集群无线传感器网络。它是一个半集中式的算法家族，在簇头的层次结构中结合定期的信任更新，空间相关性和分组序列验证，以减轻传感器节点不必要的意见查询和信任评估计算。我们比较了TrustSense与传统信誉系统（如EigenTrust）的效率，模拟结果显示，在可靠性和能量使用方面有显着改善，同时在不同数量的恶意节点下保持可接受的路径长度。我们相信，结合不同类别的入侵检测系统的不同技术的方法解锁了几种可能性，实现更好的结果，这些技术的更复杂和灵活的组合。
英文摘要：
Designing security systems for wireless sensor networks presents a challenge due to their relatively low computational resources. This has rendered many traditional defense mechanisms based on cryptography infeasible for deployment on such networks. Reputation and anomaly detection systems have been implemented as viable alternatives, but existing implementations still struggle with providing efficient security without a significant impact on energy consumption. To address this trade-off between resource consumption and resiliency, we designed TrustSense, a reputation management protocol for clustered WSNs. It is a semi-centralized family of algorithms that combine periodic trust updates, spatial correlation, and packet sequence validation at the cluster-heads' hierarchy to relieve the sensor nodes of unnecessary opinion queries and trust evaluation computation. We compared the efficiency of TrustSense with legacy reputation systems such as EigenTrust and the results of simulations show a significant improvement in reliability and energy usage while maintaining an acceptable path length with varying numbers of malicious nodes. We believe the approach of combining different techniques from various classes of intrusion detection systems unlocks several possibilities of achieving better results by more complex and versatile composition of these techniques.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
