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In order to enhance the cyber-security of networked control systems, Kogiso and Fujita (2015) proposed a concept of controller encryption using homomorphic encryption for the first time. Encrypted linear controllers using a homomorphic encryption scheme could conceal the information processed inside the controller device and maintain the original f...
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Citations
... Firstly, we adopt a fully homomorphic encryption scheme [14,15] proposed by Brakerski, Fan, and Vercauteren to encrypt the controller in this paper, which we usually refer to as BFV encryption. Secondly, we use the method of generating tables by precomputation [16] to improve encryption efficiency. Thirdly, we propose to continuously update the table to improve security. ...
... Ref. [13] considers the application of fully homomorphic encryption to NCSs to alleviate the extra overhead and quantization errors caused by quantization recovery. Subsequently, ref. [16] proposed to use a nonstrictly fully homomorphic encryption scheme for encryption and performed optimization. We refer to the method of [16] and propose a new fully homomorphic encryption scheme. ...
... Subsequently, ref. [16] proposed to use a nonstrictly fully homomorphic encryption scheme for encryption and performed optimization. We refer to the method of [16] and propose a new fully homomorphic encryption scheme. The scheme performs well in terms of security and efficiency compared to existing schemes using fully homomorphic encryption. ...
In actual operation, there are security risks to the data of the network control system, mainly in the form of possible eavesdropping of signals in the transmission channel and parameters in the controller leading to data leakage. In this paper, we propose a scheme for encrypting linear controllers using fully homomorphic encryption, which effectively removes these security risks and substantially improves the security of networked control systems. Meanwhile, this paper uses precomputation to handle data encryption, which eliminates the encryption time and solves the drawback of fully homomorphic encryption that it is difficult to apply due to the efficiency problem. Compared to previous schemes with precomputation, for the first time, we propose two methods to mitigate the problem of the slight security degradation caused by precomputation, which makes our scheme more secure. Finally, we provide numerical simulation results to support our scheme, and the data show that the encrypted controller achieves normal control and improves safety and efficiency.
The energy-efficient path selection algorithm proposed in this paper balances the conflicting goals of maximizing network lifetime and minimizing energy usage routing in mobile ad hoc networks (MANETs). The proposed strategy maximizes lifetime energy efficiency, MANET, and deep learning. Produce the data after building the network by carrying out assaults and validating paths. Then sketch a neural network with capabilities for prediction and performance evaluation. Then nodes in a network that are negative by definition must be followed by choosing the optimum route. Employed in the current study to increase the energy efficiency as well as the kind of data handling on the network with the metrics of stolen time, total time, total energy, and packet delivery rate, predict the energy and lifetime maximization utilizing deep neural networks for deep learning, management, and lifetime energy efficiency maximization. Five hundred packets of data from a neural network were used to get the maximum value. The total energy used is 7570, packets are delivered at 74.60, time taken is 371.81, and the minimum theft rate for 500 packets is 6.8.
