WAG
发表于 2025-3-23 11:50:59
https://doi.org/10.1007/978-981-99-0272-9artificial intelligence; computer security; authentification; computer crime; machine learning; computer
flamboyant
发表于 2025-3-23 15:23:25
Wanyi Gu,Guojun Wang,Peiqiang Li,Xubin Li,Guangxin Zhai,Xiangbin Li,Mingfei Chentrong-coupling problem. Namely it is the QED theory, where the correspondent problem of the “Landau pole” or the “Moscow zero” of the beta-function have led to the well known discussion about the common base of the quantum field theory.
辞职
发表于 2025-3-23 19:10:06
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disrupt
发表于 2025-3-24 02:10:10
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补助
发表于 2025-3-24 05:21:52
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染色体
发表于 2025-3-24 07:22:08
Detecting Unknown Vulnerabilities in Smart Contracts with Multi-Label Classification Model Using CNNiLSTM model. Our model determines whether a vulnerability is unknown by detecting the opcode sequence representing the entire execution process of a transaction. Experimental results with the opcode sequences of transactions show that the model can achieve 82.86% accuracy and 83.63% F1-score.
Coma704
发表于 2025-3-24 11:54:24
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iodides
发表于 2025-3-24 17:07:24
Detecting Unknown Vulnerabilities in Smart Contracts with Binary Classification Model Using Machine inally, we validate the effectiveness of our scheme by three machine learning models, namely the K-Near Neighbor Algorithm (KNN), the Support Vector Machine (SVM), and the Logistic Regression (LR). The SVM model achieves an accuracy of 91.4% and F1-score of 75.3% for the detection of unknown vulnerabilities.
Impugn
发表于 2025-3-24 19:40:58
Hierarchical Policies of Subgoals for Safe Deep Reinforcement Learningper, we combine the subgoal embedding method with REINFORCE algorithm and PPO(Proximal Policy Optimization) algorithm to test the method in the MiniGrid-DoorKey game environment of the gym platform. The experiments demonstrate the effectiveness of the subgoal embedding method.
Epithelium
发表于 2025-3-25 00:59:54
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