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

2017 ◽  
Vol 10 (13) ◽  
pp. 176 ◽  
Author(s):  
Kanchana Devi V ◽  
Ganesan R

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. 

Author(s):  
Chao Liu ◽  
Pingyu Jiang ◽  
Chaoyang Zhang

The interconnection among heterogeneous sensors and data acquisition equipment in cyber-physical systems have profound significance in achieving adaptability, flexibility, and transparency. Various middlewares have been developed in cyber-physical systems to collect, aggregate, correlate, and translate system monitoring data. Existing middleware solutions are normally highly customized, which face several challenges due to the highly dynamic and harsh production environments. The data generated by sensors can only be shared by specific applications, which prevents the reusability of sensors. Moreover, the lack of uniform access to sensors causes high cost and low efficiency in application development. To address these issues, a resource-oriented middleware architecture called ROMiddleware was proposed, and three key enabling technologies including heterogeneous sensor modeling and grouping, open application programming interfaces development, and token-based access right control mechanism have been developed. Under the guidance of the key enabling technologies, a prototype of ROMiddleware was implemented and its performance was evaluated. Finally, two applications were developed to stress the significance of ROMiddleware. The results show that ROMiddleware can meet the requirements of data acquisition in cyber-physical systems.


Author(s):  
Aisha Kanwal Junejo ◽  
Nikos Komninos ◽  
Mithileysh Sathiyanarayanan ◽  
Bhawani Shankar Chowdhry

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5463 ◽  
Author(s):  
Po-Wen Chi ◽  
Ming-Hung Wang

Cloud-assisted cyber–physical systems (CCPSs) integrate the physical space with cloud computing. To do so, sensors on the field collect real-life data and forward it to clouds for further data analysis and decision-making. Since multiple services may be accessed at the same time, sensor data should be forwarded to different cloud service providers (CSPs). In this scenario, attribute-based encryption (ABE) is an appropriate technique for securing data communication between sensors and clouds. Each cloud has its own attributes and a broker can determine which cloud is authorized to access data by the requirements set at the time of encryption. In this paper, we propose a privacy-preserving broker-ABE scheme for multiple CCPSs (MCCPS). The ABE separates the policy embedding job from the ABE task. To ease the computational burden of the sensors, this scheme leaves the policy embedding task to the broker, which is generally more powerful than the sensors. Moreover, the proposed scheme provides a way for CSPs to protect data privacy from outside coercion.


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