Forensic Analysis of Digital Dynamic Signatures: New Methods for Data Treatment and Feature Evaluation
Forensic Analysis of Digital Dynamic Signatures: New Methods for Data Treatment and Feature Evaluation
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DOI：
10.1111/1556-4029.13288
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发表时间：
2017-03-01
影响因子：
1.6
通讯作者：
Mazzella, Williams
中科院分区：
文献类型：
--
作者：
Linden, Jacques;Marquis, Raymond;Mazzella, Williams
本研究探讨包含可量化动态资料的数位动态签章。数据内容和性质的变化需要开发新的数据处理方法。使用SignPad Omega数字化平板电脑评估测量再现性，以及写入器内变化和正确模拟特征的发生。除了压力信息外，测量再现性很高。内作家的变化被发现是更高的天之间比同一天。对于特征码大小、弹道长度和总特征码时间等特征，正确模拟的发生率较低。特征鉴别因子结合内的作家的变化和正确的模拟功能的发生进行了计算，并显示，签名大小，轨迹长度和签名时间是最好的功能，用于区分真正的模拟签名。最后的实验表明，动态信息可以用来创建模拟情况之间的连接。
This study explored digital dynamic signatures containing quantifiable dynamic data. The change in data content and nature necessitates the development of new data treatment approaches. A SignPad Omega digitizing tablet was used to assess measurement reproducibility, as well as within-writer variation and the occurrence of correctly simulated features. Measurement reproducibility was found to be high except for pressure information. Within-writer variation was found to be higher between days than on a same day. Occurrence of correct simulation was low for features such as signature size, trajectory length, and total signature time. Feature discrimination factors combining within-writer variability and the occurrence of correctly simulated features were computed and show that signature size, trajectory length, and signature time are the features that perform the best for discriminating genuine from simulated signatures. A final experiment indicates that dynamic information can be used to create connections between simulation cases.