iSignDB: A biometric signature database created using smartphone

iSignDB: A biometric signature database created using smartphoneSuraiya Jabin, Sumaiya Ahmad, Sarthak Mishra, and Farhana Javed ZareenDepartment of Computer Science, Jamia Millia Islamia, New Delhi-110025, IndiaIt's a database of biometric signatures recorded using sensors present in a smartphone. The dataset iSignDB is created to implement a novel anti-spoof biometric signature authentication for smartphone users.We named it iSignDB as we collected it using a licensed MathWorks cloud account and with iOS and Android based smartphone devices (iPhone 7 Plus and Redmi Note 7) for capturing dynamic signatures.A total of 48 subjects volunteered for data collection out of which we identified 32 users as genuine signature contributors and 16 users as fake signature contributors with skilled forgery.Data was collected in 3 different sessions separated by at least 20 days in order to capture the emotional intelligence of users.During each session, one pair of subjects, out of which one subject contributed 10 original signatures and the other contributed 5 fake signatures.For obtaining a fake signature, a subject was allowed to practice copying not only the signature image of a genuine user but also the behaviorism (e.g. number of touchpoints, style of finger movement while signing, etc.) while genuine signer signs on the touch screen of a smartphone.A total of 30 genuine and 15 fake samples were collected for each of 32 users.One sign of a user contains a sensor log captured using sensors present in the smartphone: Accelerometer, Gyroscope, Magnetometer, and GPS, etc along with images of signature as obtained by performing a sign on the touch screen of the device.We have uploaded the smartphone biometric sign database of all 32 users in this repository. The full database of 32 users is available for other researchers only after they sign and submit the terms and conditions of using it.We successfully trained 32 BiGRU models on dynamic signature dataset created with EER of 0.66% which is a significant improvement.We provide Matlab code (compatible with MATLAB 2020a licensed version) for training, testing, and calculating EER in this repository (https://github.com/suraiyajabin/iSignDB2020).iSignDB is available to other researchers only after signing its "Term of use" agreement and acknowledging it properly in their work.Nomenclature for files in the dataset iSignDB: (each sign with 5 sensor logs corresponding to Acceleration, Angular Velocity, Magnetic Field, Orientation, and Position, and image of signature u01_s3_r010_AngVel.txt : means a signature of user 1, on session 3, real signature, 10th sample’s Angular velocity sensor log u01_s1_f02_MagField.txt : means a signature of user 1, on session 1, fake signature, 2nd sample’s magnetic field sensor log u01_s1_r01_im.png : image of the genuine signature of user 1, captured on session 1, sample 1iSignDB：一款基于智能手机采集的生物特征签名数据库 作者：Suraiya Jabin、Sumaiya Ahmad、Sarthak Mishra与Farhana Javed Zareen，印度新德里贾米亚·米利亚·伊斯兰大学计算机科学系，邮编110025 本数据库通过智能手机内置传感器采集生物特征签名，旨在为智能手机用户构建新型抗欺骗生物签名认证方案。本数据集之所以命名为iSignDB，是因为其采集工作依托经授权的MathWorks云账号，且使用搭载iOS与Android系统的智能手机设备（iPhone 7 Plus与Redmi Note 7）采集动态签名样本。 本次数据采集共招募48名志愿者，其中确定32名用户提供真实签名样本，16名用户提供熟练伪造的签名样本。数据采集共分为3个独立会话阶段，各阶段间隔至少20天，以捕捉用户情绪状态变化带来的签名行为差异。每个会话阶段中，每两名志愿者为一组，其中一名志愿者提供10份真实签名样本，另一名提供5份伪造签名样本。 为获取伪造签名样本，志愿者可先进行练习：不仅临摹真实用户的签名图像，还需模仿真实签名者在智能手机触摸屏上签名时的行为模式（如触摸点数、手指移动风格等）。共为32名用户各采集30份真实签名样本与15份伪造签名样本。 单份用户签名样本包含智能手机内置传感器采集的传感器日志数据，涵盖加速度计(Accelerometer)、陀螺仪(Gyroscope)、磁力计(Magnetometer)与GPS等传感器数据，同时包含在设备触摸屏上签名时采集的签名图像。 本仓库已上传全部32名用户的智能手机生物特征签名数据库。仅当其他研究人员签署并提交使用条款后，方可获取完整的32用户数据集。本研究基于构建的动态签名数据集，成功训练了32个双向门控循环单元(BiGRU)模型，等错误率(EER)仅为0.66%，性能提升显著。 本仓库同时提供适配授权版MATLAB 2020a的Matlab代码，用于数据集训练、测试与等错误率(EER)计算，代码仓库地址为：https://github.com/suraiyajabin/iSignDB2020。其他研究人员需签署iSignDB的使用条款协议，并在其研究成果中正确引用本数据集，方可获取使用权限。 iSignDB数据集的文件命名规则如下：每份签名样本包含5份传感器日志文件，分别对应加速度、角速度、磁场、方向与位置数据，同时包含签名图像文件。示例如下： 1. `u01_s3_r010_AngVel.txt`：表示用户1在会话3采集的第10份真实签名样本的角速度传感器日志文件 2. `u01_s1_f02_MagField.txt`：表示用户1在会话1采集的第2份伪造签名样本的磁场传感器日志文件 3. `u01_s1_r01_im.png`：表示用户1在会话1采集的第1份真实签名样本的签名图像文件