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Dos and Don'ts of Machine Learning in Computer Security., , , , , , , and . CoRR, (2020)EC2: Ensemble Clustering and Classification for Predicting Android Malware Families., , and . IEEE Trans. Dependable Secur. Comput., 17 (2): 262-277 (2020)A Data-driven Characterization of Modern Android Spyware., , , , and . ACM Trans. Manag. Inf. Syst., 11 (1): 4:1-4:38 (2020)TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time., , , , and . USENIX Security Symposium, page 729-746. USENIX Association, (2019)Dos and Don'ts of Machine Learning in Computer Security., , , , , , , and . USENIX Security Symposium, page 3971-3988. USENIX Association, (2022)Intriguing Properties of Adversarial ML Attacks in the Problem Space., , , and . CoRR, (2019)Enabling Fair ML Evaluations for Security., , , , and . ACM Conference on Computer and Communications Security, page 2264-2266. ACM, (2018)Detection and Threat Prioritization of Pivoting Attacks in Large Networks., , , and . IEEE Trans. Emerg. Top. Comput., 8 (2): 404-415 (2020)Scalable Architecture for Multi-User Encrypted SQL Operations on Cloud Database Services., , , and . IEEE Trans. Cloud Comput., 2 (4): 448-458 (2014)Countering Advanced Persistent Threats through security intelligence and big data analytics., , , and . CyCon, page 243-261. IEEE, (2016)