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題名 物聯網零信任架構下基於賽局模型之任務卸載
Task Offloading Based on Game Model in Zero Trust IoT Networks
作者 謝博丞
Xie, Bo-Cheng
貢獻者 孫士勝
Sun, Shi-Sheng
謝博丞
Xie, Bo-Cheng
關鍵詞 物聯網
任務卸載
邊緣運算
賽局理論
零信任架構
Internet of Things (IoT)
Task Offloading
Edge Computing (EC)
Game Theory (GT)
Zero Trust Architecture (ZTA)
日期 2025
上傳時間 1-Sep-2025 16:56:02 (UTC+8)
摘要 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.
參考文獻 [1]Y. Chen, J. Hu, J. Zhao, and G. Min, “QoS-Aware Computation Offloading in LEO Satellite Edge Computing for IoT: A Game-Theoretical Approach,” Chin. J. Electron., vol. 33, no. 4, pp. 875–885, Jul. 2024. [2]S. Shahhosseini et al., “Exploring computation offloading in IoT systems,” Inf. Syst., vol. 107, p. 101860, Jul. 2022. [3]S. Jošilo and G. Dán, “Joint Management of Wireless and Computing Resources for Computation Offloading in Mobile Edge Clouds,” IEEE Trans. Cloud Comput., vol. 9, no. 4, pp. 1507–1520, Oct. 2021. [4]Y. Hui, Z. Su, T. H. Luan, C. Li, G. Mao, and W. Wu, “A Game Theoretic Scheme for Collaborative Vehicular Task Offloading in 5G HetNets,” IEEE Trans. Veh. Technol., vol. 69, no. 12, pp. 16044–16056, Feb. 2020. [5]C. Chi, Y. Wang, X. Tong, M. Siddula, and Z. Cai, “Game Theory in Internet of Things: A Survey,” IEEE Internet Things J., vol. 9, no. 14, pp. 12125–12146, Jul. 2022. [6]M. Samaniego and R. Deters, “Zero-Trust Hierarchical Management in IoT,” in 2018 IEEE International Congress on Internet of Things (ICIOT), San Francisco, CA: IEEE, pp. 88–95, Jul. 2018. [7]J. Zhang, X. Huang, and R. Yu, “Optimal Task Assignment With Delay Constraint for Parked Vehicle Assisted Edge Computing: A Stackelberg Game Approach,” IEEE Commun. Lett., vol. 24, no. 3, pp. 598–602, Mar. 2020. [8]S. Rose, O. Borchert, S. Mitchell, and S. Connelly, “Zero Trust Architecture,” National Institute of Standards and Technology, Aug. 2020. [9]H. Sedjelmaci, S. M. Senouci, and T. Taleb, “An Accurate Security Game for Low-Resource IoT Devices,” IEEE Trans. Veh. Technol., vol. 66, no. 10, pp. 9381–9393, Oct. 2017. [10]H. Sedjelmaci and N. Ansari, “Zero Trust Architecture Empowered Attack Detection Framework to Secure 6G Edge Computing,” IEEE Netw., pp. 1–13, 2023. [11]A. Moubayed, A. Refaey, and A. Shami, “Software-Defined Perimeter (SDP): State of the Art Secure Solution for Modern Networks,” IEEE Netw., vol. 33, no. 5, pp. 226–233, Sep. 2019. [12]D. Puthal, S. P. Mohanty, P. Nanda, and U. Choppali, “Building Security Perimeters to Protect Network Systems Against Cyber Threats [Future Directions],” IEEE Consum. Electron. Mag., vol. 6, no. 4, pp. 24–27, Oct. 2017. [13]M. Wooldridge, “Does Game Theory Work?,” IEEE Intell. Syst., vol. 27, no. 6, pp. 76–80, Jan. 2012. [14]V. Sankaranarayanan, M. Chandrasekaran, and S. Upadhyaya, “Towards Modeling Trust Based Decisions: A Game Theoretic Approach,” in Computer Security – ESORICS 2007, J. Biskup and J. López, Eds., Berlin, Heidelberg: Springer, 2007, pp. 485–500.. [15]Y. Bai, L. Chen, L. Song, and J. Xu, “Risk-Aware Edge Computation Offloading Using Bayesian Stackelberg Game,” IEEE Trans. Netw. Serv. Manag., vol. 17, no. 2, pp. 1000–1012, Jun. 2020. [16]D. Perumalsamy, S. Johnson, and R. Thinakaran, “Unraveling health impacts of individuals in industrial zones: Leveraging game theory-based LSTM approach for predictive analysis of public health dynamics,” Ain Shams Eng. J., vol. 16, no. 10, p. 103579, Oct. 2025. [17]Y. Shen et al., “Game-theoretic analytics for privacy preservation in Internet of Things networks: A survey,” Eng. Appl. Artif. Intell., vol. 133, p. 108449, Jul. 2024. [18]N. Nisan, T. Roughgarden, É. Tardos, and V. Vazirani, Eds., Algorithmic game theory. Cambridge University Press, 2007. [19]L. Xiao, T. Chen, G. Han, W. Zhuang, and L. Sun, “Game Theoretic Study on Channel-Based Authentication in MIMO Systems,” IEEE Trans. Veh. Technol., vol. 66, no. 8, pp. 7474–7484, Aug. 2017. [20]H. Zhou, Z. Wang, N. Cheng, D. Zeng, and P. Fan, “Stackelberg-Game-Based Computation Offloading Method in Cloud–Edge Computing Networks,” IEEE Internet Things J., vol. 9, no. 17, pp. 16510–16520, Sep. 2022. [21]Z. A. E. Houda, B. Brik, A. Ksentini, L. Khoukhi, and M. Guizani, “When Federated Learning Meets Game Theory: A Cooperative Framework to Secure IIoT Applications on Edge Computing,” IEEE Trans. Ind. Inform., vol. 18, no. 11, pp. 7988–7997, Jan. 2022. [22]D. Cao, P. Liang, T. Wu, S. Zhang, and L. Zhou, “Enhancing trust and security in IoT computing offloading through game theory and blockchain-based control strategy,” Concurr. Comput. Pract. Exp., vol. 36, no. 15, p. e7956, 2024. [23]Z. Liao, X. Han, X. Tang, and C. Feng, “An Adaptable Pricing-Based Resource Allocation Scheme Considering User Offloading Needs in Edge Computing,” IEEE Internet Things J., vol. 12, no. 1, pp. 582–594, Jan. 2025. [24]M. Tao, K. Ota, M. Dong, and H. Yuan, “Stackelberg Game-Based Pricing and Offloading in Mobile Edge Computing,” IEEE Wirel. Commun. Lett., vol. 11, no. 5, pp. 883–887, May 2022. [25]L. Wu, P. Sun, Z. Wang, Y. Li, and Y. Yang, “Computation Offloading in Multi-Cell Networks With Collaborative Edge-Cloud Computing: A Game Theoretic Approach,” IEEE Trans. Mob. Comput., vol. 23, no. 3, pp. 2093–2106, Mar. 2024. [26]L. Zhou, Y. Chen, K. Li, Y. Yang, and J. Huang, “Stackelberg Game-Based Computation Offloading in Urban IoT Systems With UAV-Assisted Multi-Access Edge Computing,” IEEE Internet Things J., pp. 1–1, 2024. [27]R. Rani, S. Kumar, and U. Dohare, “Trust Evaluation for Light Weight Security in Sensor Enabled Internet of Things: Game Theory Oriented Approach,” IEEE Internet Things J., vol. 6, no. 5, pp. 8421–8432, Oct. 2019. [28]Y. Wang, L. Tian, and Z. Chen, “Game Analysis of Access Control Based on User Behavior Trust,” Information, vol. 10, no. 4, Art. no. 4, Apr. 2019. [29]J. He et al., “Application of Game Theory in Integrated Energy System Systems: A Review,” IEEE Access, vol. 8, pp. 93380–93397, 2020. [30]Y. Jie, C. Guo, K.-K. R. Choo, C. Z. Liu, and M. Li, “Game-Theoretic Resource Allocation for Fog-Based Industrial Internet of Things Environment,” IEEE Internet Things J., vol. 7, no. 4, pp. 3041–3052, Apr. 2020.
描述 碩士
國立政治大學
資訊科學系
110753139
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110753139
資料類型 thesis
dc.contributor.advisor 孫士勝zh_TW
dc.contributor.advisor Sun, Shi-Shengen_US
dc.contributor.author (Authors) 謝博丞zh_TW
dc.contributor.author (Authors) Xie, Bo-Chengen_US
dc.creator (作者) 謝博丞zh_TW
dc.creator (作者) Xie, Bo-Chengen_US
dc.date (日期) 2025en_US
dc.date.accessioned 1-Sep-2025 16:56:02 (UTC+8)-
dc.date.available 1-Sep-2025 16:56:02 (UTC+8)-
dc.date.issued (上傳時間) 1-Sep-2025 16:56:02 (UTC+8)-
dc.identifier (Other Identifiers) G0110753139en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/159408-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學系zh_TW
dc.description (描述) 110753139zh_TW
dc.description.abstract (摘要) 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。zh_TW
dc.description.abstract (摘要) 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.en_US
dc.description.tableofcontents Chapter1 Introduction 1 1.1 Internet Of Things 1 1.2 Traffic Offloading 1 1.3 Motivation 2 1.4 Contributions 3 1.5 Thesis Organization 3 Chapter2 Related Work 5 2.1 Zero Trust Architecture 5 2.2 Game Theory 10 2.3 Literatures Comparison 14 Chapter3 System Model 18 3.1 System Environment 19 3.2 Task And Computation Model 20 3.3 Game Model 23 Chapter4 Problem Formation And Analysis 25 4.1 Problem Formulation 25 4.2 Problem Analysis 26 Chapter5 Task Offloading Algorithm 31 5.1 Optimal Computation Offloading Decisions 31 5.2 Gradient-Descent Pricing Algorithm 33 Chapter6 Performance Evaluation 37 6.1 Parameters Settings 37 6.2 Convergence And Parameter Analysis 38 6.3 Malicious Iot Devices Analysis 46 Chapter7 Conclusion And Future Work 49 7.1 Conclusion 49 7.2 Future Work 50 REFERENCES 52zh_TW
dc.format.extent 1542543 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110753139en_US
dc.subject (關鍵詞) 物聯網zh_TW
dc.subject (關鍵詞) 任務卸載zh_TW
dc.subject (關鍵詞) 邊緣運算zh_TW
dc.subject (關鍵詞) 賽局理論zh_TW
dc.subject (關鍵詞) 零信任架構zh_TW
dc.subject (關鍵詞) Internet of Things (IoT)en_US
dc.subject (關鍵詞) Task Offloadingen_US
dc.subject (關鍵詞) Edge Computing (EC)en_US
dc.subject (關鍵詞) Game Theory (GT)en_US
dc.subject (關鍵詞) Zero Trust Architecture (ZTA)en_US
dc.title (題名) 物聯網零信任架構下基於賽局模型之任務卸載zh_TW
dc.title (題名) Task Offloading Based on Game Model in Zero Trust IoT Networksen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) [1]Y. Chen, J. Hu, J. Zhao, and G. Min, “QoS-Aware Computation Offloading in LEO Satellite Edge Computing for IoT: A Game-Theoretical Approach,” Chin. J. Electron., vol. 33, no. 4, pp. 875–885, Jul. 2024. [2]S. Shahhosseini et al., “Exploring computation offloading in IoT systems,” Inf. Syst., vol. 107, p. 101860, Jul. 2022. [3]S. Jošilo and G. Dán, “Joint Management of Wireless and Computing Resources for Computation Offloading in Mobile Edge Clouds,” IEEE Trans. Cloud Comput., vol. 9, no. 4, pp. 1507–1520, Oct. 2021. [4]Y. Hui, Z. Su, T. H. Luan, C. Li, G. Mao, and W. Wu, “A Game Theoretic Scheme for Collaborative Vehicular Task Offloading in 5G HetNets,” IEEE Trans. Veh. Technol., vol. 69, no. 12, pp. 16044–16056, Feb. 2020. [5]C. Chi, Y. Wang, X. Tong, M. Siddula, and Z. Cai, “Game Theory in Internet of Things: A Survey,” IEEE Internet Things J., vol. 9, no. 14, pp. 12125–12146, Jul. 2022. [6]M. Samaniego and R. Deters, “Zero-Trust Hierarchical Management in IoT,” in 2018 IEEE International Congress on Internet of Things (ICIOT), San Francisco, CA: IEEE, pp. 88–95, Jul. 2018. [7]J. Zhang, X. Huang, and R. Yu, “Optimal Task Assignment With Delay Constraint for Parked Vehicle Assisted Edge Computing: A Stackelberg Game Approach,” IEEE Commun. Lett., vol. 24, no. 3, pp. 598–602, Mar. 2020. [8]S. Rose, O. Borchert, S. Mitchell, and S. Connelly, “Zero Trust Architecture,” National Institute of Standards and Technology, Aug. 2020. [9]H. Sedjelmaci, S. M. Senouci, and T. Taleb, “An Accurate Security Game for Low-Resource IoT Devices,” IEEE Trans. Veh. Technol., vol. 66, no. 10, pp. 9381–9393, Oct. 2017. [10]H. Sedjelmaci and N. Ansari, “Zero Trust Architecture Empowered Attack Detection Framework to Secure 6G Edge Computing,” IEEE Netw., pp. 1–13, 2023. [11]A. Moubayed, A. Refaey, and A. Shami, “Software-Defined Perimeter (SDP): State of the Art Secure Solution for Modern Networks,” IEEE Netw., vol. 33, no. 5, pp. 226–233, Sep. 2019. [12]D. Puthal, S. P. Mohanty, P. Nanda, and U. Choppali, “Building Security Perimeters to Protect Network Systems Against Cyber Threats [Future Directions],” IEEE Consum. Electron. Mag., vol. 6, no. 4, pp. 24–27, Oct. 2017. [13]M. Wooldridge, “Does Game Theory Work?,” IEEE Intell. Syst., vol. 27, no. 6, pp. 76–80, Jan. 2012. [14]V. Sankaranarayanan, M. Chandrasekaran, and S. Upadhyaya, “Towards Modeling Trust Based Decisions: A Game Theoretic Approach,” in Computer Security – ESORICS 2007, J. Biskup and J. López, Eds., Berlin, Heidelberg: Springer, 2007, pp. 485–500.. [15]Y. Bai, L. Chen, L. Song, and J. Xu, “Risk-Aware Edge Computation Offloading Using Bayesian Stackelberg Game,” IEEE Trans. Netw. Serv. Manag., vol. 17, no. 2, pp. 1000–1012, Jun. 2020. [16]D. Perumalsamy, S. Johnson, and R. Thinakaran, “Unraveling health impacts of individuals in industrial zones: Leveraging game theory-based LSTM approach for predictive analysis of public health dynamics,” Ain Shams Eng. J., vol. 16, no. 10, p. 103579, Oct. 2025. [17]Y. Shen et al., “Game-theoretic analytics for privacy preservation in Internet of Things networks: A survey,” Eng. Appl. Artif. Intell., vol. 133, p. 108449, Jul. 2024. [18]N. Nisan, T. Roughgarden, É. Tardos, and V. Vazirani, Eds., Algorithmic game theory. Cambridge University Press, 2007. [19]L. Xiao, T. Chen, G. Han, W. Zhuang, and L. Sun, “Game Theoretic Study on Channel-Based Authentication in MIMO Systems,” IEEE Trans. Veh. Technol., vol. 66, no. 8, pp. 7474–7484, Aug. 2017. [20]H. Zhou, Z. Wang, N. Cheng, D. Zeng, and P. Fan, “Stackelberg-Game-Based Computation Offloading Method in Cloud–Edge Computing Networks,” IEEE Internet Things J., vol. 9, no. 17, pp. 16510–16520, Sep. 2022. [21]Z. A. E. Houda, B. Brik, A. Ksentini, L. Khoukhi, and M. Guizani, “When Federated Learning Meets Game Theory: A Cooperative Framework to Secure IIoT Applications on Edge Computing,” IEEE Trans. Ind. Inform., vol. 18, no. 11, pp. 7988–7997, Jan. 2022. [22]D. Cao, P. Liang, T. Wu, S. Zhang, and L. Zhou, “Enhancing trust and security in IoT computing offloading through game theory and blockchain-based control strategy,” Concurr. Comput. Pract. Exp., vol. 36, no. 15, p. e7956, 2024. [23]Z. Liao, X. Han, X. Tang, and C. Feng, “An Adaptable Pricing-Based Resource Allocation Scheme Considering User Offloading Needs in Edge Computing,” IEEE Internet Things J., vol. 12, no. 1, pp. 582–594, Jan. 2025. [24]M. Tao, K. Ota, M. Dong, and H. Yuan, “Stackelberg Game-Based Pricing and Offloading in Mobile Edge Computing,” IEEE Wirel. Commun. Lett., vol. 11, no. 5, pp. 883–887, May 2022. [25]L. Wu, P. Sun, Z. Wang, Y. Li, and Y. Yang, “Computation Offloading in Multi-Cell Networks With Collaborative Edge-Cloud Computing: A Game Theoretic Approach,” IEEE Trans. Mob. Comput., vol. 23, no. 3, pp. 2093–2106, Mar. 2024. [26]L. Zhou, Y. Chen, K. Li, Y. Yang, and J. Huang, “Stackelberg Game-Based Computation Offloading in Urban IoT Systems With UAV-Assisted Multi-Access Edge Computing,” IEEE Internet Things J., pp. 1–1, 2024. [27]R. Rani, S. Kumar, and U. Dohare, “Trust Evaluation for Light Weight Security in Sensor Enabled Internet of Things: Game Theory Oriented Approach,” IEEE Internet Things J., vol. 6, no. 5, pp. 8421–8432, Oct. 2019. [28]Y. Wang, L. Tian, and Z. Chen, “Game Analysis of Access Control Based on User Behavior Trust,” Information, vol. 10, no. 4, Art. no. 4, Apr. 2019. [29]J. He et al., “Application of Game Theory in Integrated Energy System Systems: A Review,” IEEE Access, vol. 8, pp. 93380–93397, 2020. [30]Y. Jie, C. Guo, K.-K. R. Choo, C. Z. Liu, and M. Li, “Game-Theoretic Resource Allocation for Fog-Based Industrial Internet of Things Environment,” IEEE Internet Things J., vol. 7, no. 4, pp. 3041–3052, Apr. 2020.zh_TW