Infrared sensors capture thermal radiation emitted by objects. They can operate in all weather conditions and are thus employed in fields such as military surveillance, autonomous driving, and medical diagnostics. However, infrared imagery poses challenges such as low contrast and indistinct textures due to the long wavelength of infrared radiation and susceptibility to interference. In addition, complex enhancement algorithms make real-time processing challenging. To address these problems and improve visual quality, in this paper, we propose a multi-scale FPGA-based method for real-time enhancement of infrared images by using rolling guidance filter (RGF) and contrast-limited adaptive histogram equalization (CLAHE). Specifically, the original image is first decomposed into various scales of detail layers and a base layer using RGF. Secondly, we fuse detail layers of diverse scales, then enhance the detail information by using gain coefficients and employ CLAHE to improve the contrast of the base layer. Thirdly, we fuse the detail layers and base layer to obtain the image with global details of the input image. Finally, the proposed algorithm is implemented on an FPGA using advanced high-level synthesis tools. Comprehensive testing of our proposed method on the AXU15EG board demonstrates its effectiveness in significantly improving image contrast and enhancing detail information. At the same time, real-time enhancement at a speed of 147 FPS is achieved for infrared images with a resolution of 640 × 480.

Dual-beam circularly polarized antenna arrays are widely demanded in high-capacity wireless and satellite communication systems. However, conventional designs typically suffer from complex feeding networks, large profile, and high insertion loss, which limit their integration level and efficiency. To address these issues, this paper proposes a low-loss, highly integrated dual-beam circularly polarized antenna array based on a substrate-integrated waveguide equivalent ENZ feeding network. A new physical phenomenon is revealed that the tangential electric field in the slots exhibits an equal-amplitude and anti-phase distribution due to the combined effect of the uniform field distribution in the ENZ medium and the boundary conditions of the slotted perfect electric conductor. Using this inherent mechanism, the antenna achieves symmetric dual-beam radiation at approximately ±27° in the E-plane. A polarization conversion meta surface layer is loaded to convert linear polarization into circular polarization. A prototype is fabricated and measured. At 8.3 GHz, the measured peak gain is 9.1 dBi, the minimum axial ratio is better than 1.5 dB, and the radiation efficiency is higher than 85%. The proposed array features simple structure, low loss, and high integration. Compared with conventional feeding structures, it eliminates the need for additional phase shifters or power dividers, effectively reducing insertion loss and structural complexity. It exhibits good application potential in compact base stations and satellite communication terminals.

As underwater platforms become increasingly networked and autonomous, reliable and physically secure links are emerging as critical engineering infrastructure for ocean observation, offshore energy, and maritime security. Underwater wireless optical communication (UWOC) addresses the bandwidth–latency gap left by acoustic systems, yet most existing implementations operate at fixed rates and cannot adapt to dynamic underwater channels. This study presents a real-time multi-rate adaptive bidirectional (time-divided) UWOC system implemented on field-programmable gate arrays (FPGAs). A DC-biased optical orthogonal frequency-division multiplexing (DCO-OFDM) physical layer with four switchable formats (BPSK, 4-QAM, 8-QAM, and 16-QAM) is combined with a pilot-free blind SNR estimation algorithm exploiting virtual carriers and an ACK/NAK stop-and-wait automatic repeat request (ARQ) protocol. The system autonomously adjusts its physical rate between 10 and 100 Mbps across a maximum single-pass water attenuation of 54.8 dB. The narrow line-of-sight beam geometry and tight receiver field of view further offer inherent spatial filtering against eavesdropping, positioning the system as a candidate secure multi-modal component of underwater communication networks. Outdoor-pool experiments with an optical attenuation coefficient of 1.37 dB/m, certified by the China Electronic Product Reliability and Environmental Testing Research Institute (CEPREI, the Fifth Electronics Research Institute of MIIT), demonstrated a mean BER ≤ 1.8 × 10⁻⁶ in all four modes, with every individual certified run below the 10⁻⁵; criterion (worst single run: 5.4 × 10⁻⁶). These results establish a real-time hardware proof of concept validated in an outdoor pool, constituting a step toward field-deployable adaptive underwater optical links in marine engineering scenarios—AUV docking, subsea infrastructure inspection, and underwater sensor networks—and provide a verified platform on which physical-layer security extensions can be built.

We examine whether simulated attack-action evidence can inform a defender that they must commit before an attacker’s type is known. We formulate a five-stage Bayesian Stackelberg security game with five stage-specific actions per player. A Monte Carlo predictor produces type-conditioned action likelihoods on an enterprise graph, while prediction confidence weights the next Bayesian update. The defender strategy is computed by exact follower-response enumeration and linear programming. Evaluation used a simulated 10-node enterprise network, 30 paired trials, bootstrap confidence intervals, and Holm-adjusted Wilcoxon tests. Against a fixed-prior Bayesian Strong Stackelberg Equilibrium, mean gross defense utility increased from 2.141 to 2.197. Mean attack success decreased from 0.691 to 0.686. The paired differences remained significant after multiplicity correction. Outcomes did not differ significantly from an equilibrium updated with coarse reference likelihoods, and the simulation cost reduced net utility by 0.08. Maximum follower regret and constraint violation remained at the specified numerical tolerance. Runtime remained near 0.39 s across networks of 10–100 nodes. An action/type experiment showed rapid growth as follower-response profiles increased. Exact commitment and sequential updating were feasible in the abstraction; simulation was not automatically cost-effective when a usable reference model was available.

Proactive cyber defense requires defenders to anticipate attacker behavior and respond before breaches occur. However, existing game-theoretic models rarely integrate attack behavior simulation with temporal-aware payoff structures. This paper proposes a Stackelberg game framework for proactive cyber defense that combines Monte Carlo-based attack behavior simulation with a multi-stage, time-discounted payoff function. The defender, modeled as the Stackelberg leader, commits to an optimal mixed strategy by leveraging simulation-derived attack path predictions across five Cyber Kill Chain (CKC) stages over a 5-action defense space (|A_D| = 5) against five attacker actions (|A_A| = 5). A simulation confidence factor S quantifies prediction accuracy and is embedded directly into the defender payoff function, creating incentive-compatible alignment between simulation quality and strategic gain. Bayesian belief updates—augmented with simulation evidence—enable real-time attacker type inference under incomplete information. A fictitious play algorithm with provable convergence computes the Strong Stackelberg Equilibrium (SSE). Experimental results on a 10-node network demonstrate that the proposed framework reduces response latency by 22.9% and achieves a 4.9% payoff gain compared to Bayesian Nash Equilibrium (BNE) baselines, with convergence at 199 iterations versus 354 for BNE—a 43.8% reduction.