High Accuracy Detection of Mobile Malware Using Machine Learning / / Suleiman Yerima, editor.

• TeilnehmendeR: Yerima, Suleiman,
• Place / Publishing House: [Place of publication not identified] : : MDPI - Multidisciplinary Digital Publishing Institute,, 2023.
• Year of Publication: 2023
• Language: English
• Physical Description: 1 online resource (226 pages)
• ISBN: 3036571744
• Hierarchical level: Monograph
• Statement of Responsibility: Suleiman Yerima, editor.

As increasingly sophisticated and evasive malware attacks continue to emerge, more effective detection solutions to tackle the problem are being sought through the application of advanced machine learning techniques. This reprint presents several advances in the field including: a new method of generating adversarial samples through byte sequence feature extraction using deep learning; a state-of-the-art comparative evaluation of deep learning approaches for mobile botnet detection; a novel visualization-based approach that utilizes images for Android botnet detection; a study on the detection of drive-by exploits in images using deep learning; etc. Furthermore, this reprint presents state-of-the-art reviews about machine learning-based detection techniques that will increase researchers' knowledge in the field and enable them to identify future research and development directions.