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Duplicates in the Drebin Dataset and Reduction in the Accuracy of the Malware Detection Models.

, , , and . APCC, page 161-165. IEEE, (2021)

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Malware Detection using Machine Learning and Deep Learning., , , and . CoRR, (2019)Designing Adversarial Robust and Explainable Malware Detection System for Android based Smartphones: PhD Forum Abstract.. IPSN, page 412-413. ACM, (2021)Deep Reinforcement Learning for Cybersecurity Threat Detection and Protection: A Review., , and . CoRR, (2022)Detection of Malicious Android Applications: Classical Machine Learning vs. Deep Neural Network Integrated with Clustering., , , and . CoRR, (2021)Identification of Significant Permissions for Efficient Android Malware Detection., , , and . CoRR, (2021)Credit Card Fraud Detection Using K-Means Combined with Supervised Learning., , , , and . HIS, volume 420 of Lecture Notes in Networks and Systems, page 262-272. Springer, (2021)Towards Robust Android Malware Detection Models using Adversarial Learning., and . PerCom Workshops, page 424-425. IEEE, (2021)Identification of Adversarial Android Intents using Reinforcement Learning., , , and . IJCNN, page 1-8. IEEE, (2021)GreenForensics: Deep hybrid edge-cloud detection and forensics system for battery-performance-balance conscious devices., , and . Digit. Investig., 43 (Supplement): 301445 (2022)Robust Malware Detection Models: Learning from Adversarial Attacks and Defenses., , , and . Digit. Investig., (2021)