Handling Dynamic Environment Changes for Behavior-Based User Authentication

Description: This environment-independent user authentication dataset is from our MASS 2020 paper: Towards Environment-independent Behavior-based User Authentication Using WiFi. This dataset contains the physiological characteristics captured by WiFi from 10 participants for 10 different activities. Each participant performs 20 rounds for each activity. The experiments are conducted in two different environments, the campus office, and the home apartment. The system performance is tested on the cross-environment scenarios (training in one environment and testing in another environment). Note: The MASS 2020 paper is based on our MobiHoc 2017 paper, Smart User Authentication through Actuation of Daily Activities Leveraging WiFi-enabled IoT. The MobiHoc 2017 work focused on user authentication using CSI extracted from human activity while the MASS 2020 work focused on the domain adaptation of user authentication using activity CSI. The dataset of our MobiHoc 2017 work is also published: https://zenodo.org/record/7750976#.ZBfTZ3bMKUk Format: .dat format Section 1: Device Configuration Two commercial laptops, Dell E6430, as transmitter and receiver. Run with a Linux 14.04 operating system with 4.2.0 kernel. Equipped with 3 MINI PCI-E internal antennas. Intel 5300 network interface card (NIC) for CSI collection. The detail information regarding the CSI tool can be found at https://dhalperi.github.io/linux-80211n-csitool/faq.html. WiFi packet transmission is set to 1000 pkts/s Section 2: Data Format We provide raw data received by the CSI tool. The data files are saved in the dat format. The details are shown in the following: 10 participants are included in two different experiments. Each participant performed 20 rounds for each activity. The dataset file name is presented as "User_Day_Action_Location". The detailed information as: User: The participants that CSI was collected from. Day: The date this data was collected. Action: The specific activity performed. Location: The specific location the experiment was conducted. Section 3: Experimental Setups There are two experiment setups for our data collection. An image of the experimental setup and the illustration of activities from two different environments is included in the dataset. Each activity was performed in a designated location. In each activity location, the specific activity was conducted in 4 different proximate locations at least one foot away from each other. Residential Apartment Environment: The experiments are conducted in a residential apartment with a size 33ft × 17ft. Participant: 10 users are students from Rutgers University (aged from 20 to 30). Activity: 7 activities were performed. Detailed Activities Performed in Apartment Code Activity A→B Walking (trajectory 1) B→C Walking (trajectory 2) B Picking up a remote control C Sitting in a chair D Exercising E Operating on the oven F Using the stove Office Environment: The experiments are conducted in an office with a size 21ft × 12ft. Participant: 5 users are students from Rutgers University (aged from 20 to 30). Activity: 3 activities were performed. Detailed Activities Performed in Office Code Activity G Sitting in a seat H Stretching the body I Typing on a keyboard Section 4: Data Description We separate our raw data into different folders based on different environment types. In each environment type, data are further distributed in terms of date. Each file includes all data from three internal antennas. All data files are in .dat format. We also provide Matlab scripts for CSI analysis and visualization. The following variables can be revealed from the codes: CSI: This is the Channel State Information (CSI) received from one receiver antenna. It describes the signal propagation from the transmitter to the receiver, and it is very sensitive to the impact of environmental changes. Each data reveals CSI from 30 subcarriers. Relative Phase: Relative Phase is a measurement to describe the degree of synchronization between data received from different antennas. It can be used to determine the phase offset for further signal preprocessing. Time: This is the time interval in which the data file contains. It measures time by the number of seconds. It can be used to determine how long the signal has been received. Section 5: Codes analysis_spectrogram.m: load a .dat file and extract all data by Data description(I.e, CSI, and Relative Phase). Section 6: Citations If your paper is related to our works, please cite our papers as follows. https://ieeexplore.ieee.org/document/9356038 C. Shi, J. Liu, N. Borodinov, B. Leao and Y. Chen, "Towards Environment-independent Behavior-based User Authentication Using WiFi," 2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), Delhi, India, 2020, pp. 666-674, doi: 10.1109/MASS50613.2020.00086 Bibtex: @INPROCEEDINGS{9356038, author={Shi, Cong and Liu, Jian and Borodinov, Nick and Leao, Bruno and Chen, Yingying}, booktitle={2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)}, title={Towards Environment-independent Behavior-based User Authentication Using WiFi}, year={2020}, volume={}, number={}, pages={666-674}, doi={10.1109/MASS50613.2020.00086}} The current version of the dataset is shrunk due to its size. If you wish to acquire the full version or you have any questions regarding the dataset, contact us by email: [e-mail].

本数据集为环境无关型用户认证数据集，源自我们发表于MASS 2020的论文《面向WiFi的环境无关行为基用户认证》（Towards Environment-independent Behavior-based User Authentication Using WiFi）。该数据集包含10名参与者在10种不同活动中由WiFi采集得到的生理特征数据。每位参与者针对每项活动完成20轮实验。实验分别在两种不同环境中开展：校园办公室与家庭公寓。系统性能在跨环境场景下进行测试（即在某一环境中训练，在另一环境中测试）。
注：MASS 2020论文的工作基于我们2017年发表于MobiHoc的论文《利用支持WiFi的物联网设备驱动日常活动实现智能用户认证》（Smart User Authentication through Actuation of Daily Activities Leveraging WiFi-enabled IoT）。2017年MobiHoc的研究聚焦于利用从人类活动中提取的信道状态信息（Channel State Information，CSI）开展用户认证，而2020年MASS的研究则聚焦于基于活动CSI的用户认证领域自适应方法。我们2017年MobiHoc研究的数据集也已公开：https://zenodo.org/record/7750976#.ZBfTZ3bMKUk

数据格式：.dat格式

1. 设备配置
采用两台商用戴尔（Dell）E6430笔记本电脑分别作为发射端与接收端，运行Linux 14.04操作系统（内核版本4.2.0），搭载3个MINI PCI-E内置天线，配置Intel 5300网络接口卡（NIC）用于CSI采集。有关CSI采集工具的详细信息可参见：https://dhalperi.github.io/linux-80211n-csitool/faq.html。WiFi数据包发送速率设置为1000包/秒。

2. 数据格式
我们提供CSI采集工具接收的原始数据，数据文件以.dat格式存储，详细说明如下：本数据集包含两场不同实验的10名参与者数据。每位参与者针对每项活动完成20轮实验。数据集文件命名格式为"User_Day_Action_Location"，各字段含义如下：
- User：采集CSI数据的参与者身份
- Day：数据采集日期
- Action：参与者执行的具体活动
- Location：实验开展的具体环境位置

3. 实验设置
本次数据采集包含两种实验设置，数据集中附带实验场景实拍图与两种环境下的活动示意图。每项活动均在指定位置开展，且每个活动场景下，实验均在至少相距1英尺的4个邻近位置中完成。
（1）住宅公寓环境：实验在尺寸为33ft×17ft的住宅公寓内开展。参与者为10名罗格斯大学（Rutgers University）学生，年龄介于20至30岁之间。共开展7项活动，公寓内活动详情如下：
| 活动代码 | 活动内容 |
| ---- | ---- |
| A→B | 沿轨迹1行走 |
| B→C | 沿轨迹2行走 |
| B | 拿起遥控器 |
| C | 坐在椅子上 |
| D | 进行体育锻炼 |
| E | 操作烤箱 |
| F | 使用炉灶 |

（2）办公室环境：实验在尺寸为21ft×12ft的办公室内开展。参与者为5名罗格斯大学学生，年龄介于20至30岁之间。共开展3项活动，办公室内活动详情如下：
| 活动代码 | 活动内容 |
| ---- | ---- |
| G | 坐在座椅上 |
| H | 拉伸身体 |
| I | 在键盘上打字 |

4. 数据描述
我们将原始数据按照不同环境类型划分至不同文件夹中，每个环境类型下的数据再按采集日期进一步分类。每个文件包含来自3个内置天线的全部数据，所有数据文件均为.dat格式。我们还提供用于CSI分析与可视化的Matlab脚本，通过该脚本可提取以下变量：
- 信道状态信息（CSI）：从单根接收天线采集得到的信道状态信息，描述信号从发射端到接收端的传播特性，对环境变化的影响极为敏感。每份数据包含30个子载波的CSI信息。
- 相对相位（Relative Phase）：用于描述不同天线接收数据间的同步程度，可用于确定相位偏移以开展后续信号预处理。
- 时间（Time）：数据文件涵盖的时间区间，以秒为单位计量，可用于确定信号接收时长。

5. 代码
`analysis_spectrogram.m`：加载.dat文件，并根据数据描述（即CSI与相对相位）提取全部数据。

6. 引用说明
若您的研究工作与本数据集相关，请按以下方式引用我们的论文：
https://ieeexplore.ieee.org/document/9356038
C. Shi, J. Liu, N. Borodinov, B. Leao and Y. Chen, "Towards Environment-independent Behavior-based User Authentication Using WiFi," 2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), Delhi, India, 2020, pp. 666-674, doi: 10.1109/MASS50613.2020.00086

Bibtex引用格式：
@INPROCEEDINGS{9356038, author={Shi, Cong and Liu, Jian and Borodinov, Nick and Leao, Bruno and Chen, Yingying}, booktitle={2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)}, title={"Towards Environment-independent Behavior-based User Authentication Using WiFi"}, year={2020}, volume={}, number={}, pages={666-674}, doi={10.1109/MASS50613.2020.00086}}

当前版本的数据集因文件体积限制已进行压缩。若您希望获取完整版本，或对本数据集有任何疑问，请通过电子邮件联系我们：[e-mail]。