Robust Android Malware Detection System Against Adversarial Attacks Using Q-Learning
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DOI: 10.1007/s10796-020-10083-8
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Cited by:
- Vinay Singh & Brijesh Nanavati & Arpan Kumar Kar & Agam Gupta, 2023. "How to Maximize Clicks for Display Advertisement in Digital Marketing? A Reinforcement Learning Approach," Information Systems Frontiers, Springer, vol. 25(4), pages 1621-1638, August.
- Hemant Rathore & Adithya Samavedhi & Sanjay K. Sahay & Mohit Sewak, 2023. "Towards Adversarially Superior Malware Detection Models: An Adversary Aware Proactive Approach using Adversarial Attacks and Defenses," Information Systems Frontiers, Springer, vol. 25(2), pages 567-587, April.
- Sanjay K. Sahay & Nihita Goel & Murtuza Jadliwala & Shambhu Upadhyaya, 2021. "Advances in Secure Knowledge Management in the Artificial Intelligence Era," Information Systems Frontiers, Springer, vol. 23(4), pages 807-810, August.
- Mohit Sewak & Sanjay K. Sahay & Hemant Rathore, 2023. "Deep Reinforcement Learning in the Advanced Cybersecurity Threat Detection and Protection," Information Systems Frontiers, Springer, vol. 25(2), pages 589-611, April.
- G. Kirubavathi & W. Regis Anne, 2024. "Behavioral based detection of android ransomware using machine learning techniques," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(9), pages 4404-4425, September.
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Keywords
Adversarial learning; Android; Malware detection; Machine learning; Reinforcement learning; Static analysis;All these keywords.
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