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Detecting and Analyzing Malware in Android Mobile Devices Through Network Traffic Monitoring
Abstract
Attacks by malevolent software developers have increased in tandem with the growing popularity of cell phones. This study examines several techniques these assailants employ and recommends more effective ones. Android phones are especially susceptible to these attacks since network traffic analysis isn't taken into account sufficiently in today's detection techniques. In this article, a rule-based classifier—a cutting-edge technique—that can reliably identify more than 90% of hazardous traffic is introduced. Malicious apps are becoming more and more prevalent due to the expanding black market and the increasing number of applications that are accessible. To identify questionable activity, the suggested system automatically collects and examines applications from reputable retailers or unofficial marketplaces. The research provides a clear picture of how the platform has changed over time and how well various detection techniques work. It also compares several techniques for Android malware detection.
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