面向指纹考勤机的数据取证与分析方法

顾红星; 上官梦轩; 丁锰; 何易临; 马万里

doi:10.11959/j.issn.1000-0801.DXKX250645

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面向指纹考勤机的数据取证与分析方法

研究与开发 | 更新时间：2026-05-13

- 面向指纹考勤机的数据取证与分析方法
- Data forensics and analysis method for fingerprint attendance machines
- 电信科学 2026年42卷第4期页码：117-133
- 作者机构：
  
  1.中国人民公安大学侦查学院，北京 100038
  2.温州市公安司法鉴定中心，浙江温州 325101
  3.中国人民公安大学公共安全行为科学实验室，北京 100038
- 作者简介：
  
  [ "顾红星（2002−），男，中国人民公安大学硕士生，主要研究方向为电子数据取证。" ]
  [ "上官梦轩（1992- ），男，现就职于温州市公安司法鉴定中心，主要研究方向为电子数据取证。" ]
  [ "丁锰（1980- ），男，中国人民公安大学副教授，主要研究方向为电子数据取证。" ]
  [ "何易临（2003- ），男，中国人民公安大学硕士生，主要研究方向为电子数据取证。" ]
  [ "马万里（2002- ），男，中国人民公安大学硕士生，主要研究方向为电子数据取证。" ]
- 基金信息：
  
  广东省证据材料司法鉴定（南天）工程技术研究中心开放课题基金项目(ETRC202403)
- DOI：10.11959/j.issn.1000-0801.DXKX250645
  中图分类号： TP391;TN06
- 收稿：2025-11-04，
  
  修回：2025-12-05，
  
  录用：2025-12-25，
  
  纸质出版：2026-04-20
- 稿件说明：
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顾红星,上官梦轩,丁锰等.面向指纹考勤机的数据取证与分析方法[J].电信科学,2026,42(04):117-133.

Gu Hongxing,Shangguan Mengxuan,Ding Meng,et al.Data forensics and analysis method for fingerprint attendance machines[J].Telecommunications Science,2026,42(04):117-133.
顾红星,上官梦轩,丁锰等.面向指纹考勤机的数据取证与分析方法[J].电信科学,2026,42(04):117-133. DOI： 10.11959/j.issn.1000-0801.DXKX250645.

Gu Hongxing,Shangguan Mengxuan,Ding Meng,et al.Data forensics and analysis method for fingerprint attendance machines[J].Telecommunications Science,2026,42(04):117-133. DOI： 10.11959/j.issn.1000-0801.DXKX250645.

摘要

指纹考勤机作为目前广泛应用的身份识别设备，其存储的指纹数据和考勤记录在法庭科学中具有重要的取证价值。然而，对其取证和分析面临以下3个问题：常规取证方法受限、指纹模板数据识别困难、缺少针对性的关联分析方法。针对以上问题，提出了一种面向指纹考勤机的数据取证与分析方法。首先根据指纹考勤机的存储特性，研究直连提取方法，能够直接从存储芯片中读取底层数据；其次，针对考勤机中常见的3类指纹模板，提出对应的识别方法；最后，对于考勤机内部不同类型的数据，提出异构数据的关联分析方法。实验结果表明，该方法能够突破接口限制，可实现复杂条件下的数据提取，对于指纹模板数据可实现跨设备识别，在此基础上通过关联分析能够发现涉案人的行为模式，为法庭科学取证工作提供新的思路和方法。

Abstract

As widely applied identity recognition devices

fingerprint attendance machines store fingerprint data and attendance records

which possess significant evidentiary value in forensic science. However

the forensic extraction and analysis of this data were challenged by three primary issues: the limitations of conventional extraction methods

the difficulty in identifying fingerprint template data

and the lack of targeted correlation analysis methods. To address the aforementioned issues

a data forensic and analysis method specifically for fingerprint attendance machines was proposed. Firstly

based on the storage characteristics of the attendance machines

a direct-connect extraction method was developed

by which low-level data could be read directly from the storage chip. Secondly

corresponding identification methods were propose for the three common types of fingerprint templates found in these machines. Finally

for the different types of data within the machines

a correlation analysis method for heterogeneous data was put forward. Experimental results demonstrate that interface limitations can be overcome by this method

and data extraction is achieved under complex conditions. For fingerprint template data

cross-device identification is realized. Building on this

the behavioral patterns of individuals involved could be discovered through correlation analysis. Consequently

new approaches and methodologies were provided for forensic science work.

关键词

Keywords

references

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