Biblio

With rapid development of deep integration of computation, control, and communication, Cyber-Physical Systems (CPSs) play an important role in industrial processes. Combined with the technology of fog computing, CPSs can outsource their complicated computation to the fog layer, which in turn, may bring security threats with regard to data privacy. To protect data privacy in a control framework, this paper investigate observer-based secure control problem towards fog computing aided CPSs (FCA-CPSs) by utilizing data perturbation method. Firstly, security inputs are designed to encrypt the transmitted states to realize specific confidentiality level. Then, sufficient conditions are established to ensure the stability of considered FCA-CPSs. Finally, a numerical example is provided to illustrate the effectiveness of the secure estimation scheme.

Statistics suggests, proceeding towards IoT generation, is increasing IoT devices at a drastic rate. This will be very challenging for our present-day network infrastructure to manage, this much of data. This may risk, both security and traffic collapsing. We have proposed an infrastructure with Fog Computing. The Fog layer consists two layers, using the concepts of Service oriented Architecture (SOA) and the Agent based composition model which ensures the traffic usage reduction. In order to have a robust and secured system, we have modified the Fog based agent model by replacing the SOA with secured Named Data Network (NDN) protocol. Knowing the fact that NDN has the caching layer, we are combining NDN and with Fog, as it can overcome the forwarding strategy limitation and memory constraints of NDN by the Agent Society, in the Middle layer along with Trust management.

In Smart Grids (SGs), data aggregation process is essential in terms of limiting packet size, data transmission amount and data storage requirements. This paper presents a novel Domingo-Ferrer additive privacy based Secure Data Aggregation (SDA) scheme for Fog Computing based SGs (FCSG). The proposed protocol achieves end-to-end confidentiality while ensuring low communication and storage overhead. Data aggregation is performed at fog layer to reduce the amount of data to be processed and stored at cloud servers. As a result, the proposed protocol achieves better response time and less computational overhead compared to existing solutions. Moreover, due to hierarchical architecture of FCSG and additive homomorphic encryption consumer privacy is protected from third parties. Theoretical analysis evaluates the effects of packet size and number of packets on transmission overhead and the amount of data stored in cloud server. In parallel with the theoretical analysis, our performance evaluation results show that there is a significant improvement in terms of data transmission and storage efficiency. Moreover, security analysis proves that the proposed scheme successfully ensures the privacy of collected data.