隨著物聯網（IoT）網路的蓬勃發展，感測器、設備以及伺服器的效能日益強大，然而，位於網路最外圍的IoT裝置因其固有的硬體限制，常導致運算效能低落，進而拖累整體系統效能。此外，傳統的邊界安全模型（防火牆、金鑰等）預設了內部裝置的信任，若裝置遭到入侵並變為惡意狀態時，則其難以有效應對來自惡意裝置的資料污染或是資源耗盡攻擊。本研究針對上述挑戰，提出了一種整合技術：將邊緣運算（Edge Computing，EC）環境下的任務卸載與資源配置，透過賽局理論（Game Theorem，GT）建模成策略賽局，並同時整合零信任架構（Zero Trust Architecture，ZTA）技術，以增強物聯網系統的效能並降低安全風險。其中，邊緣運算允許IoT裝置將部分運算任務卸載至算力更強大的邊緣伺服器，可降低時間延遲與能源消耗；再者，賽局理論則提供策略分析的框架，以優化資源配置並確保互動效益；最後，透過零信任架構的持續驗證機制，能有效抵禦惡意設備引入的安全威脅。本研究所整合的相關技術，不僅能針對惡意裝置構成的風險，亦能優化系統整體效能並縮短時間延遲。

Despite the rapid advancement of Internet of Things (IoT) networks, enhancing the performance of sensor, devices and servers, inherent hardware limitations at the network’s edge continue to hinder the computational efficiency of IoT devices, consequently impacting overall system performance. Furthermore, traditional perimeter security models (e.g., firewall, key), by implicitly trusting internal devices, struggle to effectively counter data poisoning or resource exhaustion attacks originating from devices that have been compromised and turned malicious. In order to overcome these challenges, this thesis proposes an innovative approach: we model task offloading and resource allocation within the Edge Computing (EC) environment as strategic interactions using Game Theory (GT), concurrently integrating Zero Trust Architecture (ZTA) techniques to comprehensively enhance the efficiency and security of the IoT systems. Specifically, the EC enables the IoT devices to partially offload computational tasks to more powerful servers, significantly reducing latency and energy consumption. Furthermore, the GT provides a strategic analysis framework to optimize resource allocation and ensure interaction efficacy. Lastly, ZTA’s continuous verification mechanism effectively defends against security threats posed by malicious devices. The integration of these techniques not only effectively mitigates risks originating from malicious entities but also simultaneously improves overall system performance and reduces time latency.

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