The one-time pad (OTP) is an application-layer encryption technique to achieve the information-theoretic security, and the physical-layer secret key generation (SKG) technique is a promising candidate to provide the random keys for OTP. In this paper, we propose a joint SKG and OTP encryption scheme with the aid of a reconfigurable intelligent surface (RIS) to boost secret key rate. To maximize the efficiency of secure communication, we divide the process of secure transmission into two stages: SKG and then encrypted packet transmission. Meanwhile, we design an optimal algorithm for allocating time slots for SKG to maximize SKG efficiency without security risk. Furthermore, we design a key updating protocol based on our SKG scheme for OTP encryption. Simulation results verify that our scheme can generate keys securely and efficiently, and significantly improve the secure communication performance in an intelligent IoT system.
The one-time pad (OTP) is an application-layer encryption technique to achieve the information-theoretic security, and the physical-layer secret key generation (SKG) technique is a promising candidate to provide the random keys for OTP. In this paper, we propose a joint SKG and OTP encryption scheme with the aid of a reconfigurable intelligent surface (RIS) to boost secret key rate. To maximize the efficiency of secure communication, we divide the process of secure transmission into two stages: SKG and then encrypted packet transmission. Meanwhile, we design an optimal algorithm for allocating time slots for SKG to maximize SKG efficiency without security risk. Furthermore, we design a key updating protocol based on our SKG scheme for OTP encryption. Simulation results verify that our scheme can generate keys securely and efficiently, and significantly improve the secure communication performance in an intelligent IoT system.
The one-time-pad (OTP) technique is widely used in the encryption to achieve the information-theoretic security, and the physical-layer secret key generation (SKG) technique can provide the random keys for OTP. However, the keys are susceptible to eavesdroppers in the correlated channel scenarios. To address this issue, this paper proposes a machine learning (ML) assisted SKG in the OTP encryption scheme. We make a complete and rigorous analysis of the information leakage under the influence of space-time correlation. The derivation based on information theory proves the security of the key generation scheme. To simplify the computational complexity, we generate the initial key based on ML. The simulation results show that the probability of information being leaked in the next frame increases if information is leaked in the current frame. Meanwhile, the simulation results verify that our ML assisted SKG scheme can generate keys securely for OTP under different space-time correlation.
The one time pad (OTP) technique can provide information-theoretic security and physical layer key generation (PLKG) is a promising candidate for OTP. In the joint PLKG and OTP scheme, channel probing, information reconciliation and encrypted packet transmission all need to occupy channel time. In this paper, we propose a time slot allocation scheme for PLKG in OTP. We divide the process of OTP into three stages: channel probing, information reconciliation and encrypted packet transmission. Then, we analyze the secret key capacity and the time slot cost of the whole process. Under the premise of ensuring safety, we give a time slot reduction strategy to reduce time slot cost. Meanwhile, we propose a time slot allocation optimization algorithm to realize the strategy. Simulation results verify that our scheme can significantly reduce the time slot cost.
The one-time pad (OTP) secure transmission relies on the random keys to achieve perfect secrecy, while the unpredictable wireless channel is shown to be a good random source. There is very few work of the joint design of OTP and key generation from wireless channels. This article provides a comprehensive and quantitative investigation on secure transmission achieved by OTP and wireless channel randomness. We propose two OTP secure transmission schemes, i.e., identical key-based physical-layer secure transmission (IK-PST) and un-IK-PST (UK-PST). We quantitatively analyze the performance of both schemes and prove that UK-PST outperforms IK-PST. We extend the pairwise schemes to a group of users in networks with star and chain topologies. We implement prototypes of both schemes and evaluate the proposed schemes through both simulations and experiments. The results verify that UK-PST has a higher effective secret transmission rate than that of IK-PST for scenarios with both pairwise and group users.
Physical layer secret key generation schemes can provide lightweight encryption for resource-constrained Internet of Things (IoT) devices. However, many IoT devices are stationary and the environment is usually static, which leads to ultra-low/zero secret key rates. To circumvent this problem, a novel secret key generation scheme based on Reconfigurable Intelligent Surface (RIS) is proposed for Multiple-Input Single-Output IoT communications. The RIS is introduced into the network, and the phase shifts at RIS are tuned randomly in each frame, which makes time-varying reflection channels superimposed on the original channels. And then, the secret key capacity of all nodes within the cell coverage area can be remarkably improved. Compared with the existing methods, the scheme is loosely coupled with the existing communication system. The closed-form expressions of secret key capacity taking into account eavesdropping are first derived for the case studies of independent and correlated channels. We can conclude that sharing the same phase shifts randomness will not bring key information leakage. Compared with existing user-introduced randomness schemes, the proposed scheme can maintain good performance as the number of eavesdropping nodes increases. Further, the impact of parameters, such as the number of reflecting units, the transmit antennas, and the Rician factor, on secret key performance are analyzed respectively, which can offer guidelines for system design. Finally, simulation results verify the theoretical analysis.
Physical layer secret key generation schemes can provide lightweight encryption for resource constrained Inter?net of Things (IoT) devices. However, many IoT devices are stationary and the environment is usually static, which leads to ultra-low/zero secret key rates. To circumvent this problem, a novel secret key generation scheme based on Reconfigurable Intelligent Surface (RIS) is proposed for Multiple-Input Single?Output IoT communications. The RIS is introduced into the network, and the phase shifts at RIS are tuned randomly in each frame, which superimpose time-varying reflection channels on the orginal channels. And then the secret key capacity of all nodes within the cell coverage area can be remarkably improved. The closed-form expressions of secret key capacity taking into account eavesdropping are first derived for the case studies of independent and correlated channels. We can conclude that sharing the same phase shifts randomness will not bring key information leakage. Compared with three benchmark schemes, the proposed scheme can both maintain good performance whenever eavesdropping nodes exist. Further, the impact of parameters, such as the number of reflecting units, the transmit antennas and the Rician factor, on secret key performance are analyzed respectively, which can offer guidelines for system design. Finally, simulation results verify the theoretical analysis.
Physical layer secret key generation (SKG) technology can provide lightweight encryption for resource-constrained Internet of Things (IoT) devices. However, many IoT devices are stationary, and the environment is usually static, which leads to ultralow/zero secret key rates. To circumvent this problem, a novel SKG scheme based on reconfigurable intelligent surface (RIS) is proposed for multiple-input single-output (MISO) communications. First, the phase shifts at the RIS are tuned randomly in each frame, which makes time-varying reflection channels superimposed on the original channels. Correspondingly, the key capacity of all nodes within the cell coverage area can be remarkably improved. Compared with the existing methods, the scheme is loosely coupled with the original system. Besides, the closed-form expressions of key capacity taking into account eavesdropping are derived for the case studies of independent and correlated channels. Based on these derivations, we can conclude that sharing the same phase shifts randomness will not lead to key information leakage. More importantly, compared with user-introduced randomness schemes, the proposed scheme can maintain good performance even the number of eavesdropping nodes increases. Furthermore, the impacts of critical parameters on key performance are analyzed, respectively, which offers guidelines for system design. Finally, simulation results verify the theoretical analysis.