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An Insightful Analysis of Digital Forensics Effects on Networks and Multimedia Applications

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Abstract

Humans have benefited greatly from technology, which has helped to raise standards of living and make important discoveries. But there are a lot of hazards associated with using it. The prevalence of digital video through mobile smartphone applications like WhatsApp and YouTube as well as web-based multimedia platforms are likewise gaining in importance as crucial. But there are also global security issues that are arising. These difficulties could cause significant issues, especially in cases where multimedia is a crucial factor in criminal decision-making, such as in child pornography and movie piracy. Consequently, copyright protection and video authentication are required in order to strengthen the reliability of using digital video in daily life. A tampered film may contain the relevant evidence in a legal dispute to convict someone of a violation or clear a guilty party of wrongdoing. Hence, to develop it is crucial to have reliable forensic techniques that would enhance the justice administration systems and enable them to reach just verdicts. This article discusses numerous forensic analysis fields, including network forensics, audio forensics, and video forensics. In this study, many algorithms such as Random Forest, Multilayer Perceptron (MLP), and Convolutional Recurrent Neural Networks (CRNN) are used for implementing different types of forensic analysis. Also, image fusion is used which can provide more information than a single image and extract features from the original images. This study came to the conclusion that the random forest provides the finest results for network forensic analysis with an accuracy of 98.02 percent. A lot of work has been done during the past years, through an analysis of current methods and machine learning strategies in the field of video source authentication and the study aims to provide a thorough summary of that work.

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Authors and Affiliations

  1. GSSSIETW, Affiliated to VTU Belagavi, Mysuru, Karnataka, India

    Aishwarya Rajeev

  2. Department of CSE, CIT, Affiliated to VTU Belagavi, Ponnampet, Karnataka, India

    Aishwarya Rajeev

  3. GSSSIETW, Affiliated to VTU Belagavi, Mysuru, Karnataka, India

    P. Raviraj

Authors
  1. Aishwarya Rajeev
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  2. P. Raviraj
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Correspondence to Aishwarya Rajeev.

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This article is part of the topical collection “Advances in Computational Intelligence for Artificial Intelligence, Machine Learning, Internet of Things and Data Analytics” guest edited by S. Meenakshi Sundaram, Young Lee and Gururaj K S.

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Rajeev, A., Raviraj, P. An Insightful Analysis of Digital Forensics Effects on Networks and Multimedia Applications. SN COMPUT. SCI. 4, 186 (2023). https://doi.org/10.1007/s42979-022-01599-8

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