## 7 Conclusions  
This paper presented a privacy-preserving polymorphic heterogeneous security architecture for cloud-edge collaborative industrial control systems that successfully addressed critical security and privacy challenges inherent in modern industrial environments. Figure 11: Individual executor voltage control outputs and final system output under the proposed method during attack scenarios. \begin{table}
\begin{tabular}{l c c c} \hline \hline
**Detection Rate (\%)** & **Average (\%)** & **Best Cases (\%)** & **Worst Cases (\%)** \\ \hline
99.9 & 99.9945 & 100.0000 & 95.0000 \\
95.4 & 99.7790 & 100.0000 & 90.0000 \\
92.9 & 99.6735 & 100.0000 & 90.0000 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Availability of SOTA MTD with different detection rates. The proposed unified framework distinguished itself from existing approaches by integrating hybrid event-time triggered scheduling with adaptive privacy-preserving arbitration, moving beyond the traditional separation of scheduling and privacy concerns that has limited the effectiveness of current DHR architectures. The architecture demonstrated three significant technical achievements through its comprehensive design. First, the hybrid event-time triggered scheduling algorithm with credibility assessment and heterogeneity metrics effectively mitigated common-mode escape scenarios that have plagued resource-constrained cloud-edge environments. Second, the adaptive privacy budget allocation mechanism successfully balanced privacy protection effectiveness with system availability, dynamically responding to varying attack activity levels. Third, the unified framework organically integrated privacy-preserving arbitration with heterogeneous redundancy management, providing a holistic solution to the dual challenges of security resilience and privacy preservation. Extensive experimental validation across natural gas pipeline pressure control and smart grid voltage control systems confirmed the architecture's superior performance, achieving 100% system availability compared to traditional approaches and maintaining 99.98% availability even under common-mode attacks. These results demonstrated the practical viability of the proposed approach in real-world industrial scenarios where both security and privacy are paramount concerns. The practical implications of this work extend beyond the specific industrial control systems examined in this study. The architectural principles developed herein have significant potential for adoption across diverse industrial domains where cloud-edge collaboration is increasingly prevalent. Different industrial applications present varying requirements for security, privacy, and real-time performance: process control systems may prioritize availability and fault tolerance, while data-intensive manufacturing environments may emphasize privacy protection for proprietary information. The modular design of our unified framework enables domain-specific adaptations through configurable privacy budget allocation and heterogeneity assessment parameters. However, successful deployment across different industrial sectors requires careful consideration of domain-specific constraints, including varying computational resource availability, communication latency requirements, and regulatory compliance standards. The adaptive nature of our approach provides a foundation for addressing these diverse requirements, though further research is needed to optimize the framework for specific industrial applications and their unique operational characteristics. Several promising research directions emerged from this work that warrant further investigation. First, the development of lightweight encryption alternatives specifically designed for time-critical industrial environments represents a crucial area for enhancing the practical deployment of privacy-preserving mechanisms without compromising real-time performance requirements.