Abstract
Modern criminal investigations are important and raise privacy issues in digital forensics. The goal of this study is to develop a privacy-preserving framework for digital forensics that makes it possible to balance effective investigation with individual privacy rights. In this work, we present an innovative framework for privacy-preserving digital forensics, which incorporates data minimization techniques with selective imaging and privacy-preserving data analysis methods. The approach is validated with a collection of case studies and a series of simulations, which show that the approach reduces privacy intrusions while maintaining investigative integrity. Results indicate up to a 40 % reduction in exposure of non-relevant personal data compared to traditional approaches with no loss of evidence collection quality. We recommend how to implement privacy-respecting digital forensic practices to policymakers. This paper adds practical solutions for investigators and legal professionals in ethical digital forensics.
| Original language | English |
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| Title of host publication | 2025 1st International Conference on Computational Intelligence Approaches and Applications, ICCIAA 2025 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798331523657 |
| DOIs | |
| State | Published - 2025 |
| Event | 1st International Conference on Computational Intelligence Approaches and Applications, ICCIAA 2025 - Amman, Jordan Duration: 28 Apr 2025 → 30 Apr 2025 |
Publication series
| Name | 2025 1st International Conference on Computational Intelligence Approaches and Applications, ICCIAA 2025 - Proceedings |
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Conference
| Conference | 1st International Conference on Computational Intelligence Approaches and Applications, ICCIAA 2025 |
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| Country/Territory | Jordan |
| City | Amman |
| Period | 28/04/25 → 30/04/25 |
Bibliographical note
Publisher Copyright:© 2025 IEEE.
Keywords
- data min-imization
- digital forensics
- investigative ethics
- privacy preservation
- selective imaging
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition