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Summary

DS-1258
Sherlock
External Dataset
External Data Source
BGU Cyber Security Research Center
Unknown
Unknown
55 (lowest rank is 55)

Category & Restrictions

Other
network data, sensors, wireless, mobile software
Unrestricted
true

Description


A labeled dataset with billions of records covering a wide variety of low-privileged monitorable smartphone features collected from 50 volunteers over a few years. The labels were created by having the volunteers run applications infected with malware -based on real malwares found in the wild.

The dataset is essentially a massive time-series dataset spanning nearly every single kind of software and hardware sensor that can be sampled from a Samsung Galaxy S5 smartphone, without root privileges. The dataset contains over 600 billion data points in over 10 billion data records. Some examples of the sampled sensors are:

Resource utilization per running App (CPU, memory, ...)
Call/SMS logs
Location
WiFi Signal strength
Network statistics
And many more... (see the dataset description here)
These sensors where sampled as a rate rivaling other similar datasets, some features sampled at a rate of up to once every second! More interestingly, we provide explicit labels (timestamps + descriptions) which capture exactly when malware on the device is performing its malicious activities. With these labels, you can use the dataset as a benchmark for your machine learning algorithms.

Additional Details

2.3GB
false
Unknown
cybercrime, unit of observation, malware, smartphone, personal computing, inferlink corporation, time series, sherlock, machine learning, wi fi, link layer, external data source, 1258, mobile phone, smart device, statistical data types, exploit, superuser, operating system security, physical layer protocols