Physical layer authentication is an important way to ensure the security of optical communication network. We hereby propose a scheme to realize it by measuring the variation of the bit error rate (BER) on both sides of communication. In this scheme, the legitimacy of the receiver is identified by analyzing the BER variation of the optical fiber loop based on the short-term correlation of the channels. We then simulate a 16 PSK optical transmission system with intensity modulation direct detection-orthogonal frequency division multiplexing (IMDD-OFDM). The authentication effect is analyzed in the case of disturbance and beam split, as well as replacement of optical fiber channels caused by eavesdropper (Eve). The results show that this scheme is sensitive to the three kinds of attacks. A high probability of detection (PD) and a low false alarm rate (FAR) can be obtained. The experimental results show that with the increase of the frequency test, PD and FAR tend to be stable, and the authentication effect is better with the accuracy rate 100%.

In this work, we have proposed a new physical layer encryption scheme to improve the security of optical fiber communication systems. The secrecy scheme is based on disturbance of the data cluster under the ZUC algorithm (named for Zu Chongzhi, a famous mathematician in ancient China), which is generated by optical XOR using a dual-drive Mach–Zehnder modulator (DD-MZM). A base scrambling pseudo random binary sequence (PRBS) generated by the ZUC stream cipher is introduced, which results in a better scrambling effect and randomness in the key stream of the block encryption structure. A simulation setup conducted in an encrypted transmission of the 64×64 grayscale image over 80 km of optical fiber shows that the authorized user can successfully decrypt the received signal, while the eavesdroppers cannot derive useful information with a bit error rate (BER) at approximately 0.5. In the simulation, after setting the delay compensation to 3.125 ps, a correct signal with a Q-factor as high as 11.3642 and a BER as low as 3.14295⁻³⁰ can be obtained.

With the increase in the popularity of cloud computing and big data applications, the amount of sensitive data transmitted through optical networks has increased dramatically. Furthermore, optical transmission systems face various security risks at the physical level. We propose a novel key distribution scheme based on signal-to-noise ratio (SNR) measurements to extract the fingerprint of the fiber channel and improve the physical level of security. The SNR varies with time because the fiber channel is affected by many physical characteristics, such as dispersion, polarization, scattering, and amplifier noise. The extracted SNR of the optical fiber channel can be used as the basis of key generation. Alice and Bob can obtain channel characteristics by measuring the SNR of the optical fiber channel and generate the consistent key by quantization coding. The security and consistency of the key are guaranteed by the randomness and reciprocity of the channel. The simulation results show that the key generation rate (KGR) can reach 25 kbps, the key consistency rate (KCR) can reach 98% after key post-processing, and the error probability of Eve’s key is ~50%. In the proposed scheme, the equipment used is simple and compatible with existing optic fiber links.

In this paper, the health status is studied for 26 volunteers of graduate students by calculating the average spectral radius of the finger pulse under the random matrix theory. It has been found that the average spectral radius of the pulse is higher for health status than that for unhealth status. This results are compared with the phase diagram of health which is filled in by volunteers actively.

Placement of edge computing servers at the edge of the network can reduce task transmission delay. Connecting them into a system can provide services for a wider range. However, due to the mobility of the crowd and mobile devices, the number of tasks offloaded to each edge server may be quite different, which will seriously affect the QoS of the system. To this end, we investigate the QoS improvement of the distributed edge computing system from the game-theoretic perspective and propose a multi-agent state-based learning algorithm. Firstly, by modeling the cost of an edge computing server as the deviation between its execution time and the system average execution time, we formulate the QoS improvement of the system as a state-based game where each agent competes to maximize its own utility. Then, we propose a multi-agent state-based learning algorithm to obtain the pure Nash equilibrium strategy of each agent. Finally, compared with the existing approaches, the experiments show that the proposed algorithm can improve the QoS of the distributed edge computing system.