政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/149471

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/149471

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題名:	針對Python 程式的神經網路模型作動態符號執行測試 Concolic Testing On Python Programs of Neural Network Models
作者:	紀亞妤 Chi, Ya-Yu
貢獻者:	郁方 Yu, Fang 紀亞妤 Chi, Ya-Yu
關鍵詞:	動態符號執行測試對抗式生成攻擊神經網路模型 Concolic Testing Adversarial attack Neural Network model
日期:	2023
上傳時間:	2024-02-01 10:57:09 (UTC+8)
摘要:	近年來，人工智慧（AI）的迅速進步在各個領域取得了重大突破，特別是在神經網路模型的應用方面。然而，AI 模型的廣泛應用引起了對其對抗式攻擊易受攻擊性的擔憂。本研究聚焦於採用動態符號執行測試，一種專門為實現神經網路的Python 程式設計的具體與符號執行結合的專業程式測試技術。本研究擴展了PyCT，一個針對Python 程式的基於約束的動態符號執行測試工具，以應對更廣泛的神經網路運作，包括在ReLU、Maxpooling 和tanh、Sigmoid 等神經網路中的浮點運算。其目標是系統性生成預測路徑約束並生成對應輸入，徹底探索神經網路分支，有助於識別潛在的對抗性例子。這項研究證明了，在 Python 程式中的神經網路架構中，這種方法能夠生成各種有影響力的對抗性例子的有效性。透過凸顯神經網路模型在Python 程式環境中對對抗式攻擊的易受攻擊性，有助於維護AI 驅動應用的穩定性。同時，強調了檢測和緩解潛在對抗威脅的強大測試方法的必要性，促進了在 Python 程式在更廣泛背景下開發更安全可靠的AI 模型的發展。同時，也強調了強化神經網路模型的嚴謹測試技術的重要性，以確保其在由 Python 支持的多樣應用中的可靠性。 In the era of rapid advancements in artificial intelligence (AI), neural network models have achieved notable breakthroughs. However, concerns arise regarding their vulnerability to adversarial attacks. This study focuses on enhancing Concolic Testing, a specialized technique for testing Python programs implementing neural networks. The extended tool, PyCT, now accommodates a broader range of neural network operations, including floating-point computations. By systematically generating prediction path constraints, the research facilitates the identification of potential adversarial examples. Demonstrating effectiveness across various neural network architectures, the study highlights the vulnerability of Python-based neural network models to adversarial attacks. This research contributes to securing AI-powered applications by emphasizing the need for robust testing methodologies to detect and mitigate potential adversarial threats. It underscores the importance of rigorous testing techniques in fortifying neural network models for reliable applications in Python.
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描述:	碩士國立政治大學資訊管理學系 110356043
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0110356043
資料類型:	thesis
顯示於類別:	[資訊管理學系] 學位論文

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