Enhancing Forensic Analysis of Digital Evidence Using Machine Learning: Techniques, Applications, and Challenges

Authors: Dr Pankaj Malik, Harshit Dawar, Pushpraj patel, Dishant ahuja, Aman Jain

DOI: https://doi.org/10.37082/IJIRMPS.v12.i5.230988

Short DOI: https://doi.org/gwfv5v

Country: India

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Abstract: In the digital age, the proliferation of electronic devices and the internet has led to an exponential increase in the amount and complexity of digital evidence in criminal investigations. Traditional forensic methods, while effective, often struggle to keep pace with the volume and intricacy of data involved. This paper explores the integration of machine learning techniques into digital forensic analysis, highlighting how these advanced computational methods can enhance the detection, classification, and interpretation of digital evidence.
We begin by providing an overview of digital forensics and the challenges it faces, including data overload, encryption, and the need for rapid analysis. The paper then delves into the various machine learning techniques applicable to digital forensics, such as anomaly detection, pattern recognition, and natural language processing. Case studies demonstrate the successful application of these techniques in real-world forensic scenarios, showcasing improvements in accuracy, efficiency, and scalability.
However, the use of machine learning in forensics is not without its challenges. Issues such as data quality, algorithmic bias, and the interpretability of complex models are examined, alongside the ethical and legal implications of relying on automated systems in legal contexts. The paper concludes by discussing future directions in the field, advocating for further research and the development of robust, transparent, and ethically sound machine learning tools for digital forensics.
This research underscores the potential of machine learning to transform digital forensic analysis, offering powerful tools for investigators while also highlighting the need for careful consideration of the associated risks and challenges.

Keywords: Digital Forensics, Machine Learning, Forensic Analysis, Digital Evidence, Data Mining, Pattern Recognition, Cybersecurity, Anomaly Detection, Artificial Intelligence, Feature Extraction

Paper Id: 230988

Published On: 2024-09-06

Published In: Volume 12, Issue 5, September-October 2024

Cite This: Enhancing Forensic Analysis of Digital Evidence Using Machine Learning: Techniques, Applications, and Challenges - Dr Pankaj Malik, Harshit Dawar, Pushpraj patel, Dishant ahuja, Aman Jain - IJIRMPS Volume 12, Issue 5, September-October 2024. DOI 10.37082/IJIRMPS.v12.i5.230988

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