Optical chaos communication has a physical-layer security advantage but defends passively against a malicious attack. Here, we conduct a proof-of-concept experiment of detecting the attack proactively by observing performance degradation in optical chaos communication tapped with fiber bending. Influences of the curvature radius of the bent fiber on a chaos synchronization coefficient and bit error rate are investigated. Results show that the synchronization coefficient decreases from 0.958 to 0.904 and the bit error rate increases from 1.31 × 10 −4 to 1.73 × 10 −3 under a curvature radius of 10 mm, revealing the attack. Bending fiber to this extent leads to a power loss of 1.81%, which is difficult to detect by the optical time-domain reflectometer but causes significant interference to chaos communication due to the concurrent change in the light polarization, jointly decreasing the effective optical injection strength for yielding chaos synchronization.
Optical chaos communication has a physical-layer security advantage but defends passively against a malicious attack. Here, we conduct a proof-of-concept experiment of detecting the attack proactively by observing performance degradation in optical chaos communication tapped with fiber bending. Influences of the curvature radius of the bent fiber on a chaos synchronization coefficient and bit error rate are investigated. Results show that the synchronization coefficient decreases from 0.958 to 0.904 and the bit error rate increases from 1.31 × 10 −4 to 1.73 × 10 −3 under a curvature radius of 10 mm, revealing the attack. Bending fiber to this extent leads to a power loss of 1.81%, which is difficult to detect by the optical time-domain reflectometer but causes significant interference to chaos communication due to the concurrent change in the light polarization, jointly decreasing the effective optical injection strength for yielding chaos synchronization.
Optical fiber communication was widely believed that an optical network was a good way to prevent hacking through wiretaps which intercept network data. However, fiber optic cable is not particularly secure. Various tapping methods can be used to extract data from fiber optic networks with little or no risk of detection. One of the easiest ways of intruding into a fiber optic communication link is creating a bend on the fiber cable. Even small percentage of the transmitted light acquired with the bending method is enough for recovering the data by the attacker. Though there are some techniques and devices that can track the power and intensity inside the fiber cable, these methods cannot detect an attack exploiting small leakage. Therefore, it is critical to determine a range of radii of curvature for which tapping attacks are not detectable. Though there are some studies to quantify the power loss both theoretically and numerically, as of the authors' knowledge, there has not been any experimental validation of those studies. In this respect, an experimental optical setup and a technique relying on the ADC conversion capability of Arduino UNO to measure power loss resulting from different bending radii are proposed in this paper. A lower limit for radius of curvature for an attack to be undetected is obtained and the estimations in the literature for power loss resulting from fiber bending is validated.
Optical fiber communication is not as secure as generally perceived. There are a number of known methods of extracting or injecting information into a fiber link, while avoiding detection. Few incidents have been reported as a successfully tapped fiber is difficult to detect. In this paper we highlight a number of known fiber tapping methods. We report simulation of optical characteristics of a fiber being tapped by `bend' method and proof of concept with physical experiment. We also presented visualized scenarios in which a resourceful eavesdropper can compromise security of a fiber link with existing technologies. Some measures to prevent fiber tapping or to nullify the significance of information tapped from fiber were also discussed.
This paper proposes a physics-informed convolutional network (PICN) scheme to detect bending eavesdropping attacks in dual-polarization coherent optical communication systems. We present a theoretical model for optical signal transmission under bending eavesdropping, analyzing the impact of bending eavesdropping on fiber physical characteristics such as dispersion and nonlinear effect. These physical characteristics are embedded into a convolutional neural network (CNN) to construct PICN, which automatically captures subtle variations of the signal features under bending eavesdropping. To validate the effectiveness of the scheme, we first develop an eavesdropping experimental platform in an 80-km 168 Gbps dual-polarization quadrature phase shift keying (QPSK) coherent optical communication system. Polarization data are then collected under normal transmission, 10.8 mm and 15 mm bending radius. Finally, the detection performance of four classifiers including PICN, random forest (RF), support vector machine (SVM), and K-nearest neighbor (KNN) are evaluated at single and mixed bending radii. Experimental results demonstrate that PICN achieves detection accuracies of 100%, 98.53%, and 99.02% under 10.8 mm, 15 mm, and mixed bending radii, respectively. Our work provides novel theoretical foundations and innovative perspectives for bending eavesdropping detection in optical fiber communication systems.
Optical fiber communication networks are the backbone of information transmission, carrying over 90% of the world's data. However, optical fibers are susceptible to fiber-bending eavesdropping attacks, which can result in massive data leaks. The detection of fiber-bending eavesdropping attacks has become one of the effective strategies to safeguard data security. In this paper, we propose a detection scheme based on a convolutional neural network (CNN) for detecting fiber-bending eavesdropping attacks in dual-polarization coherent optical communication systems. To validate the feasibility and effectiveness of the proposed scheme, we first establish the relationship between the fiber-bending radius and the bending power loss coefficient. Based on this relationship, a 100 km, 25 GBaud dual-polarization 16 quadrature amplitude modulation (16QAM) coherent optical communication system is constructed. This system collects both normal polarization data and bending eavesdropping polarization data. Subsequently, the performance of the CNN algorithm in detecting fiber-bending eavesdropping attacks is evaluated. The results show that under bending radii of 10.8 mm, 12.1 mm, 15 mm, and mixed bending radii, the eavesdropping detection accuracy rates of the CNN reach 99.8%, 99.67%, 99.22%, and 96.15%, respectively.
Optical fiber communication is the only technical means of supporting high transmission rates. Since optical fibers are insulators and can resist electromagnetic interference, they were once considered to be highly secure. However, due to the endless means of eavesdropping, optical fibers are vulnerable to eavesdropping, which poses a serious threat to the data security of optical fiber communication infrastructures. Optical fiber eavesdropping detection is one of the strategies to effectively safe transmission of data. Due to insufficient mining of eavesdropping information or limited by the performance of the sensor, it cannot be detected with high accuracy. To deal with this problem, we propose a convolutional neural networks-based scheme for de-tecting fiber bending eavesdropping in 16QAM coherent optical communication systems. Numerical results show 99.1%, 99%, and 98.5% detection accuracy at bending radii of 10.8 mm, 12.1 mm, and 15 mm, respectively.
We propose a chaotic spatial symbol transforming encryption method for enhancing the physical layer security in fiber-optic systems based on space-division multiplexed (SDM) transmission. The designed 3-D chaotic sequences are used to scramble the real and imaginary part of quadrature amplitude modulation (QAM) symbols, permute the symbol-to-space mapping, and control iteration times between the two processes. The encrypted transmission of 200 Gb/s per mode polarization-division-multiplexed 16QAM signals has been simulated over 1000-km two-mode fiber. The results show that the eavesdropper cannot recover the original information with a part of the security keys or a part of the transmitted signals when the iteration times are beyond 5. We found the error spreading phenomenon can be combined with the mode-dependent loss (MDL) to realize the system security enhancement. When eavesdroppers coupled signals out from SDM waveguide by bending-induced fiber tapping, they need reduce the bend radius to receive more spatial leak modes. The bending-induced fiber tapping inherently causes MDL. Although the error spreading phenomenon leads to bit-error-rate increasing by 1.3 dB than conventional 16QAM transmission, it will be a promising solution to overcome the weakness that the huge amount of data can be compromised by taping out the portion of the signal in single-mode transmission.