AEACFE System—An Intelligent Digital Forensic System

  • Shruti B. YagnikEmail author
  • Esan P. PanchalEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 797)


The significant increase in cyber crime has led to an increasing demand for researches to be done on cyber forensics. Cyber forensic investigation paradigm is laborious and requires significant expertise on the part of the investigators. There are various cyber forensic tools that are available in the market to analyze cyber forensic evidences. Those tools need manual intervention to make analysis and generate reports accordingly. Analysis of cyber forensic evidences needs to be automated such that investigator can directly conclude cyber forensic case. Taking and preserving evidences and analyzing evidences become a need of the hour. This paper highlights the various phases in which automation is a substitute for manual evidence taking and analysis. Evidences are automatically taken and analyzed without much intervention of the investigators. This method makes use of special kind of machine learning algorithms which aids in these situations. Machine learning algorithm analyzes digital evidences and presents hidden features to digital forensic investigators that may useful to make decision of digital forensic crime. Hence, this work is a complete fusion of cyber forensics and machine learning.


Automation Cyber crime Cyber forensics Evidences Forensic investigations Machine learning algorithms 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Computer Science and Engineering DepartmentCalorx Teachers’ UniversityAhmedabadIndia
  2. 2.Computer Science and Engineering DepartmentRai UniversityAhmedabadIndia

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