Effectiveness of machine learning based android malware detectors against adversarial attacks

Ankit Jyothish; Ashik Mathew; P. Vinod

doi:10.1007/s10586-023-04086-8

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Effectiveness of machine learning based android malware detectors against adversarial attacks

Ankit Jyothish Ashik Mathew P. Vinod

Year: 2023 Journal: Cluster Computing Vol: 27 (3)Pages: 2549-2569 Publisher: Springer Science+Business Media

DOI: 10.1007/s10586-023-04086-8

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Keywords:

Computer science Artificial intelligence Random forest Machine learning Autoencoder Malware Extreme learning machine Deep learning Adversarial machine learning n-gram Classifier (UML) Undersampling Pattern recognition (psychology) Artificial neural network Computer security Language model

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Advanced Malware Detection Techniques

Physical Sciences → Computer Science → Signal Processing

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Software Testing and Debugging Techniques

Physical Sciences → Computer Science → Software

Effectiveness of machine learning based android malware detectors against adversarial attacks

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