Abstract:The widespread occurrence of mobile malware still poses a significant security threat to billions of smartphone users. To counter this threat, several machine learning-based detection systems have been proposed within the last decade. These methods have achieved impressive detection results in many settings, without requiring the manual crafting of signatures. Unfortunately, recent research has demonstrated that these systems often suffer from significant performance drops over time if the underlying distribut… Show more
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