OSX malware detection : Challenges and solutions
Author:
Affiliation:
1. Department of Computer Science & Engineering, KIET Group of Institutions, Ghaziabad 201206, Uttar Pradesh India
2. Department of Computer Science & Engineering, KIET Group of Institutions, Ghaziabad 201206, Uttar Pradesh India,
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/02522667.2020.1723942
Reference18 articles.
1. A hybrid-multi filter-wrapper framework to identify run-time behaviour for fast malware detection
2. Leveraging Support Vector Machine for Opcode Density Based Detection of Crypto-Ransomware
3. iABC-AL: Active learning-based privacy leaks threat detection for iOS applications
4. Classification of ransomware families with machine learning based onN-gram of opcodes
5. Riasat, Rubata, et al. “Onamd: An Online Android Malware Detection Approach.” 2018 International Conference on Machine Learning and Cybernetics (ICMLC). Vol. 1. IEEE, 2018.
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