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A GENERIC TRUST MANAGEMENT FRAMEWORK FOR HETEROGENEOUS SENSORS IN CYBER PHYSICAL SYSTEMS

机译:网络物理系统中异构传感器的通用信任管理框架

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Objective : “Wireless Technology” is the magic word in today’s era. In which, Cyber Physical Systems (CPS) is the booming world which binds the physical world and cyber world together. The CPS is also called as Safety Critical System because of the human life involvement. In this emerging technology, lots of heterogeneous sensors are involved and each sensor will play an important role. If something goes wrong with sensor or sensor data. It will definitely affect the human life involved in it. Methods : In this paper, we proposed a generic trust management framework for heterogeneous sensors which will detect the sensor data falsification (Data Integrity), faulty sensor reading, and packet dropping nodes (Selfish Nodes) through rules and rating concept. Results : The efficiency of the proposed framework is evaluated with the help of Network Simulator 2 (NS-2.35). The maximum numbers of untrusted nodes are identified in point 0.40 than Multi-Level Trust Framework for Wireless Sensor Network (MTF-WSN) and Framework for Packet-Droppers Mitigation (FPDM). It is also evident that Trust Management Framework for Cyber Physical Systems (TRMF-CPS) identifies maximum number of untrusted nodes in the detection range of 0.35 and 0.45. Therefore, 0.35 and 0.45 are considered as maximum and minimum threshold points for effective untrusted nodes. Conclusion: The experimentation results and comparative study shows that, our trust management framework will easily detected sensors which misbehave.
机译:目标:“无线技术”是当今时代的魔咒。其中,网络物理系统(CPS)是一个蓬勃发展的世界,它将物理世界和网络世界捆绑在一起。由于涉及人类生命,CPS也被称为安全关键系统。在这项新兴技术中,涉及许多异构传感器,每个传感器都将发挥重要作用。如果传感器或传感器数据出了问题。它肯定会影响其中的人类生活。方法:在本文中,我们为异构传感器提出了一个通用的信任管理框架,该框架将通过规则和评级概念来检测传感器数据篡改(数据完整性),传感器读取错误以及数据包丢弃节点(Selfish节点)。结果:借助网络模拟器2(NS-2.35)评估了所提出框架的效率。在比无线传感器网络多级信任框架(MTF-WSN)和数据包缓解框架(FPDM)更高的点0.40中,确定了不受信任节点的最大数量。同样明显的是,网络物理系统信任管理框架(TRMF-CPS)在检测范围0.35和0.45中确定了最大不受信任节点数。因此,将0.35和0.45视为有效不受信任节点的最大和最小阈值点。结论:实验结果和比较研究表明,我们的信任管理框架可以轻松检测出行为不当的传感器。

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