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Leveraging Spectral Representations of Control Flow Graphs for Efficient Analysis of Windows Malware.

, , , and . AsiaCCS, page 1240-1242. ACM, (2022)

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Leveraging Spectral Representations of Control Flow Graphs for Efficient Analysis of Windows Malware., , , and . AsiaCCS, page 1240-1242. ACM, (2022)The Impact of Model Variations on the Robustness of Deep Learning Models in Adversarial Settings., , , , and . SVCC, page 1-7. IEEE, (2024)ShellCore: Automating Malicious IoT Software Detection Using Shell Commands Representation., , , , , , , , and . IEEE Internet Things J., 9 (4): 2485-2496 (2022)Black-box and Target-specific Attack Against Interpretable Deep Learning Systems., , , and . AsiaCCS, page 1216-1218. ACM, (2022)Hardening Interpretable Deep Learning Systems: Investigating Adversarial Threats and Defenses., , , , and . IEEE Trans. Dependable Secur. Comput., 21 (4): 3963-3976 (2024)MLxPack: Investigating the Effects of Packers on ML-based Malware Detection Systems Using Static and Dynamic Traits., , , , and . CySSS@AsiaCCS, page 11-18. ACM, (2022)Soteria: Detecting Adversarial Examples in Control Flow Graph-based Malware Classifiers., , , , , , and . ICDCS, page 888-898. IEEE, (2020)MotionID: Towards practical behavioral biometrics-based implicit user authentication on smartphones., , , and . Pervasive Mob. Comput., (2024)Unmasking the Vulnerabilities of Deep Learning Models: A Multi-Dimensional Analysis of Adversarial Attacks and Defenses., , , , and . SVCC, page 1-8. IEEE, (2024)Investigating Online Toxicity in Users Interactions with the Mainstream Media Channels on YouTube., , , and . CIKM (Workshops), volume 2699 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)