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Machine Learning Meets iOS Malware: Identifying Malicious Applications on Apple Environment.

, , and . ICISSP, page 487-492. SciTePress, (2017)

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Real-Time SCADA Attack Detection by Means of Formal Methods., , and . WETICE, page 231-236. IEEE, (2019)Keystroke Analysis for User Identification using Deep Neural Networks., , , and . IJCNN, page 1-8. IEEE, (2019)Privacy-Preserving LDA Classification over Horizontally Distributed Data., , , and . IDC, volume 868 of Studies in Computational Intelligence, page 65-74. Springer, (2019)On absence of diffusion for low energy for a random Schrödinger operator on L2(R), and . Physica A: Statistical and Theoretical Physics, 124 (1-3): 413--417 (March 1984)Introducing Usage Control in MQTT., , , , and . CyberICPS/SECPRE@ESORICS, volume 10683 of Lecture Notes in Computer Science, page 35-43. Springer, (2017)Image-based Malware Family Detection: An Assessment between Feature Extraction and Classification Techniques., , , and . IoTBDS, page 499-506. SCITEPRESS, (2020)Dependability in dynamic, evolving and heterogeneous systems: the connect approach., , , , and . SERENE, page 83-88. ACM, (2010)Classification of ransomware families with machine learning based on N-gram of opcodes., , , , , and . Future Gener. Comput. Syst., (2019)Handling Meta Attribute Information in Usage Control Policies (Short Paper)., , , , , , and . ETAA, volume 13136 of Lecture Notes in Computer Science, page 143-151. Springer, (2021)Evaluating Fuzzy Machine Learning for Smart Grid Instability Detection., , and . FUZZ, page 1-6. IEEE, (2023)