## 3 Key Findings
### What Security Enhancement Could the Quantum Mechanism Offer the IIoT Ecosystem?
#### 3.3.3 Quantum Deployment in IIoT
In a general term, QCL could be categorized into three: classical learning with quantum data [34; 90], quantum speed-ups for classical learning [34; 89; 115], and quantum algorithms used on quantum data [113]. In the first category, quantum data are fed into a classical learning algorithm. An instance is the construction of many-body systems using AI [116] or the estimation of physical parameters in quantum metrology [117]. The second category is the potential capability of quantum information processors to produce unclonable patterns and also recognize patterns that are classically undistinguishable [118]. For example, classical data could be encoded as quantum states to quantize \begin{table}
\begin{tabular}{p{42.7 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Citations** & **Architecture** & **Attack Types** & **Security Types/Tools** & **Contributions** & **Limitations** \\ \hline \multirow{4}{*}{[35]} & Proposed QKD for large-scale networks (QLSN) protocol & \multirow{4}{*}{Eavesdropping} & QLSN was validated in the IBM Qiskit simulator & Risk minimization and reliability maximization in an LSN. It outperformed the DH key exchange. & No data was reported used \\ \hline \multirow{4}{*}{[4]} & Logistic system optimization & \multirow{4}{*}{NA} & QAOA and quantum neural network (QNN) & Securely classify industrial data with QNN. And instant predictive decision-making with QAOA & Non-in-depth practical approach \\ \hline \multirow{4}{*}{[7]} & Rawal Liang and Peter’s (RLP) sequence for QKD & DDoS, Backdoor, Injection, Ransomware, XSS, Scanning & Time-sensitive QKD & Digital twins, and quantum cryptography were jointly applied for IIoTsec, alongside QKD & No Sum Sequence approach \\ \hline \multirow{4}{*}{[111]} & Multi-party collaborative signature from lattice hard & Quantum algorithm attacks, Reply attacks, Immersion & \multirow{4}{*}{Data integrity and authentication} & Supports multiparty signatures and public auditing. Proved the unforgeability, conditional privacy preservation, and deterrability of the new protocol in the random oracle are hard \\ \cline{1-1} \cline{3-3}  & Multi-state qubit QKD model & MIMD, photon number splitting (PNS) attacks, and faked state attacks & Confidentiality and Integrity. Java snippet & Virtualize the generation and transmission of qubits, thus reducing the key generation’s computational complexity. While with QKD’s security enhancement, attacks are discarded & Secure key exchanges between IIoT devices were only executed in a non-present intruder environment \\ \hline \multirow{4}{*}{[93]} & Enhanced Quantum Particle Swarm Optimization Algorithm & \multirow{4}{*}{NA} & Proposed EQPSO to actualize reliability, bio-inspired techniques for IIoT networks & Only optimized deployments of sensor and fog nodes in IIoT environments \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Applications of Quantum Mechanisms in IIoT. (NA: Not available.). algorithms. The last category of QCL is when both the algorithms and training data are based on quantum mechanisms. QNNs are mostly deployable for this task [119]. Though this category promises better efficiency and scalability, the hunt for the optimal quantum versions of neurons, network structures, and training algorithms remains open research for the research community [113]. Unfortunately, to the best of our knowledge, and as of the time of writing this paper, no study has comprehensively considered the deployment of QCL in the IIoT ecosystem. However, very few works discuss a narrow part of QCL in an industrial sector, which is insufficient to generalize. Meanwhile, the authors [120] pointed out the potential of QCL, such as QNN, to improve performance, reduce processing time, and identify adversaries in material science, financial predictive analytics, medical precision, and pharmaceutical structure. As a result, related works of QCL are henceforth discussed. [PERSON] et al.