Sherlock

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.本数据集为超大规模时序数据集，涵盖了无需获取root权限即可从三星Galaxy S5智能手机中采集的几乎所有软硬件传感器数据。该数据集包含超100亿条数据记录，总计超过6000亿个数据点。可采集的传感器示例包括：各运行应用的资源占用情况（CPU、内存等）、通话与短信日志、位置信息、WiFi信号强度、网络统计数据等（详见本数据集官方描述文档）。该数据集的传感器采样速率可媲美同类数据集，部分特征的采样频率最高可达每秒1次！更具价值的是，本数据集附带精准标注信息（含时间戳与活动描述），可准确标记设备中恶意软件执行恶意活动的具体时刻。依托此类标注，该数据集可作为机器学习算法的评测基准数据集使用。

搜集汇总

背景与挑战

背景概述

Sherlock是一个大规模标记数据集，包含超过6000亿个数据点，覆盖了从50名志愿者的三星Galaxy S5智能手机收集的低权限传感器数据，如资源利用率、位置和WiFi信号强度。数据集通过感染恶意软件的应用程序创建标签，专注于恶意软件活动的时间戳和描述，适用于机器学习算法基准测试。