Sensor networks increasingly combine exposed sensing nodes, optical communication, photonic hardware, near-sensor inference, and distributed infrastructure monitoring. This changes the security problem from protecting packets alone to establishing device provenance, measurement integrity, link confidentiality and availability, trustworthy inference, physical situational awareness, lifecycle control, and governance. This structured review with documented scoping searches examines security by light: mechanisms in which optical or photonic phenomena directly realize, constrain, compute, or observe a security-relevant function. The review synthesizes screened evidence across photonic roots of trust, visible-light communication and LiFi security, photonic intelligence, reservoir and chaotic photonics, and distributed photonic sensing infrastructure. Searches across arXiv, IEEE Xplore, ACM Digital Library, and Scopus yielded 228 deduplicated candidate records, of which 187 were retained as core evidence and eight as contextual evidence. To avoid overstating heterogeneous photonic work, retained records were separated into direct security evidence, security-adjacent capability evidence, background/framework evidence, and excluded records. The central result is architectural: light-enabled mechanisms are most defensible when they provide explicit, confidence-rated evidence to conventional security engineering. In this paper, confidence-rated evidence means evidence whose security interpretation is tied to a stated asset, adversary or failure mode, evidence role, validation setting, robustness limits, deployment fit, and reproducibility condition. This avoids treating optical novelty, spatial confinement, analog complexity, or high-dimensional dynamics as assurance by themselves. The paper develops an auditable taxonomy, evidence appraisal rubric, mechanism-family synthesis, integration architecture, maturity analysis, and research agenda for incorporating light-enabled mechanisms into secure sensor-networked systems.

This paper introduces a novel Physical Layer Security (PLS) framework tailored for LiFi-based sensor networks within industrial environments. The proposed system comprises multiple sensor nodes, each equipped with at least three radar sensors integrating both infrared (IR) and visible light communication (VLC) subsystems. The IR subsystem employs a handshake protocol, activating the IR transmitter when data is ready for transmission and ensuring the receiver is prepared to establish a secure link. Upon successful IR handshake, the VLC subsystem initiates data communication between sensors. Additionally, the IR subsystem monitors for mobile obstacles, pausing transmission if discontinuities are detected, thereby maintaining link integrity. Environmental factors, such as walls, significantly influence the secrecy rate performance; hence, the system utilizes parallel alignment of transmitters and receivers to optimize the signal-to-background ratio. The proposed system is examined by simulation and the feasibility results are presented. The results shows that this architecture enhances the robustness and security of inter-sensor communication in challenging industrial settings. 

Light Fidelity (LiFi) offers a high-speed, interference-resistant alternative to conventional wireless communication, making it well-suited for sensitive environments such as healthcare, defense, and industrial systems. While LiFi's confinement to line-of-sight communication provides a natural layer of physical security, it remains susceptible to local eavesdropping and insider interception within its coverage area. These limitations underscore the need for additional data-level protection strategies that align with LiFi's operational constraints. This paper introduces a novel steganographic method tailored for data structured in matrix form, a common representation in many digital systems. To demonstrate the effectiveness of the proposed technique, images-naturally represented as two-dimensional matrices-are used as test cases. The approach avoids traditional payload embedding, which can be statistically detectable, and instead applies recursive segmentation, matrix reshaping, and hierarchical tree-based indexing to transform the structure of the data itself. This process produces encrypted outputs that appear statistically random and visually unstructured (i.e., noise-like), concealing both the data content and the presence of hidden communication. Quantitative evaluations using metrics such as entropy, correlation coefficients, contrast, homogeneity, and Bhattacharya distance confirm that while the encrypted data is statistically obfuscated, the original matrix can be losslessly reconstructed through inverse recursion. The method's design ensures lightweight processing is suitable for resource-constrained LiFi-enabled sensor nodes while significantly enhancing communication confidentiality. By restructuring data at the matrix level rather than embedding within it, this approach provides an effective and generalizable framework for secure transmission in physically exposed but bandwidth-rich LiFi networks.