邏輯鎖定是一種用於矽智財、積體電路的保護技術，防止硬體安全問題。近年，受惠於硬體製造技術的進步以及在機器學習中的應用，臨界值邏輯再次引起了學術界的關注。儘管有許多用於臨界值邏輯的電子設計自動化技術，但目前尚無針對臨界值邏輯的邏輯鎖定研究。在這篇論文中，我們首先提出了兩種用於鎖定臨界值邏輯閘以抵抗布林滿足性攻擊的方法，布林滿足性攻擊是對邏輯鎖定最具威脅的攻擊技術之一。第一種方法是基於整數線性規劃的方法，將臨界值邏輯閘加密問題轉換為整數線性規劃問題。由於整數線性規劃不適用於大型臨界值邏輯閘，因此我們進一步提出啟發式方法提高其效率。第二種方法是一種非基於整數線性規劃的方法，可以針對特定的臨界值邏輯閘進行鎖定或混淆，以抵抗布林滿足性攻擊和移除攻擊。基於臨界值邏輯閘鎖定方法，我們進一步提出了用於臨界值邏輯閘網路的鎖定流程。實驗結果顯示，基於整數線性規劃的方法，在可接受的執行時間內成功地加密具有少於八個輸入的臨界值邏輯閘。此外，臨界值邏輯閘網路的鎖定流程有效地使已鎖定的臨界值邏輯閘網路能夠抵抗布林滿足性攻擊。

Logic locking is an IP/IC protection technique that can prevent hardware security issues. Recently, threshold logic has re-attracted attention from researchers due to its promising hardware implementation and its applications in machine learning. While several electronic design automation techniques for threshold logic, research on logic locking specifically for threshold logic is still lacking. Therefore, in this thesis, we first propose two methods for locking a threshold logic gate (TLG) to resist SAT attack, which is one of the most powerful attack techniques against logic locking. The first method is an integer linear programming (ILP)-based method that formulates the problem of TLG encryption as an ILP problem. Since the ILP formulation is not scalable to large TLGs, we further improve its efficiency with some heuristics. The second method is a non-ILPbased method that encrypts and obfuscates specific TLGs to defend against SAT attack and Removal attack simultaneously. Based on the TLG locking methods, we further present an encryption flow for threshold logic networks (TLNs). The experimental results show that the ILP-based method can successfully encrypt the TLGs having less than 8 inputs with acceptable execution time. Additionally, the proposed TLN encryption method is effective in making the locked TLNs achieve good resistance against SAT attack.

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