Behavioural patterns

This dataset aims to provide researchers with the essential information to aid in the development and improvement surrounding system call pattern detection for crypto ransomware on Android.

Our dataset provides two sets of extracted and formatted system call logs. The first set consists of system call logs collected from 213 crypto ransomware and the second set consist of 502 benign Android applications.

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We define personal risk detection as the timely identification of when someone is in the midst of a dangerous situation, for example, a health crisis or a car accident, events that may jeopardize a person’s physical integrity. We work under the hypothesis that a risk-prone situation produces sudden and significant deviations in standard physiological and behavioural user patterns. These changes can be captured by a group of sensors, such as the accelerometer, gyroscope, and heart rate.

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