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PrivTrace: Differentially Private Trajectory Synthesis by Adaptive Markov Models.

, , , , , , и . USENIX Security Symposium, стр. 1649-1666. USENIX Association, (2023)

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Michael Backes

Michael Backes

Michael Backes

Michael Backes

Hans-Michael Backes

 

Другие публикации лиц с тем же именем

Membership Inference Attacks by Exploiting Loss Trajectory., , , и . CCS, стр. 2085-2098. ACM, (2022)Statically Detecting JavaScript Obfuscation and Minification Techniques in the Wild., , , и . DSN, стр. 569-580. IEEE, (2021)ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models., , , , , и . NDSS, The Internet Society, (2019)A Tale of Two Headers: A Formal Analysis of Inconsistent Click-Jacking Protection on the Web., , , , и . USENIX Security Symposium, стр. 683-697. USENIX Association, (2020)PrivTrace: Differentially Private Trajectory Synthesis by Adaptive Markov Models., , , , , , и . USENIX Security Symposium, стр. 1649-1666. USENIX Association, (2023)Stealing Links from Graph Neural Networks., , , , и . USENIX Security Symposium, стр. 2669-2686. USENIX Association, (2021)Membership Privacy for Fully Dynamic Group Signatures., , и . ACM Conference on Computer and Communications Security, стр. 2181-2198. ACM, (2019)AnoA: A Framework for Analyzing Anonymous Communication Protocols., , , , и . J. Priv. Confidentiality, (2016)Periodicity detection in irregularly sampled light curves by robust regression and outlier detection., , , и . Stat. Anal. Data Min., 6 (1): 73-89 (2013)On the Security Relevance of Initial Weights in Deep Neural Networks., , , , и . ICANN (1), том 12396 из Lecture Notes in Computer Science, стр. 3-14. Springer, (2020)