# Quantum-Secure Coherent Optical Networking for Advanced Infrastructures in Industry 4.0
## 2 State of the Art
### Emerging Solutions: Quantum and Adaptive Technologies  
Traditional security mechanisms in optical transport networks are limited, and therefore, advanced solutions have been explored. Thus, quantum key distribution (QKD),  
Figure 2: OTU4 framing and Modbus protocol weaknesses.  
usually tamper-proof quantum key exchanges by using quantum mechanics [15; 18], is a promising way to mitigate quantum threats. To illustrate the severity of quantum threats, consider a practical attack scenario: With [PERSON]'s algorithm, an adversary with quantum computing abilities could aim at both the MACsec and OTU4 encryption layers simultaneously. For instance, enlisting the services of a sufficiently potent quantum computer with enough qubits to factor the RSA keys to be used in both layers of the key exchange protocols would take hours, compared to the countless years that it would take classical computers. Both encryption layers are vulnerable to this because they generally use the same public key cryptographic primitives in their initial key establishment and thus represent a single point of failure, even though the encryption layers appear separate. The practical integration of QKD in high-speed optical environments, however, is challenged by scalability, a limited key rate, and compatibility with existing protocols like MACsec [16].  
In parallel, adaptive technologies such as Network Function Virtualization (NFV) and Software-Defined Networking (SDN) are proposed to improve the security and flexibility of optical transport networks. NFV and SDN decouple network functions from dedicated hardware, and, therefore, can dynamically detect and respond to threats [24; 25]. SDN architectures allow centralized control, which supports the scalability of more advanced security frameworks. Machine learning models can enhance these frameworks even further by identifying anomalies in network traffic and proactively mitigating sophisticated attacks [21; 26; 27].  
An architectural overview of the emerging security solution in optical networks is shown in Figure 3. QKD was integrated with NFV and SDN for the integrated security framework, as depicted in the diagram, and it is demonstrated how these technologies operate together to provide a comprehensive security framework.  
QKD comes with inherent theoretical security advantages, but current techniques need several practical improvements on the network optical layer. Some of these are distance limitations, key rate constraints, and infrastructure integration complexities with existing infrastructure. While NFV and SDN solutions hold promise for dynamic security  
Figure 3: Emerging solution in optical security, integrating QKD, NFV, and SDN in an optical network security architecture.  
management, they also bring their own vulnerabilities of greater network complexity and enlarged attack surfaces. While machine learning approaches can be effective for anomaly detection, they must be designed to achieve appropriate false positive rates and with acceptable computational overhead for high-speed optical environments.