Python For Digital Forensics With Daubert Standard - Nugraha, Arya Adhi; Kristomo, Domy (Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika), 2024)
Digital forensics plays a crucial role in modern investigations, where digital evidence often holds the key to solving complex cases. Python, with its versatility and extensive libraries, has emerged as a powerful tool in the realm of digital forensics. This journal explores the integration of Python into digital forensic practices, focusing on its application in conjunction with the Daubert Standard, a legal criterion for the admissibility of expert testimony. The journal begins by outlining the fundamentals of digital forensics, discussing its methodologies and tools. It then delves into the utility of Python in digital forensic investigations, highlighting key libraries and demonstrating its capabilities through practical examples. Furthermore, the journal provides an overview of the current trends in worldwide forensics, emphasizing the increasing reliance on digital evidence and the growing demand for skilled digital forensic practitioners. It explores how advancements in technology and the proliferation of digital devices have expanded the scope and complexity of forensic investigations on a global scale. A thorough examination of the Daubert Standard follows, elucidating its criteria and implications within the legal context of digital forensics. Drawing upon real-world cases, the journal illustrates the application of the Daubert Standard in assessing the reliability and validity of digital forensic evidence. Furthermore, the journal explores the symbiotic relationship between Python and the Daubert Standard, elucidating how Python scripts and methodologies can be designed to meet the rigorous standards of admissibility and reliability mandated by Daubert. Best practices for utilizing Python in a manner consistent with legal requirements are presented, emphasizing the importance of transparency, reproducibility, and peer review. In conclusion, this journal provides insights into the convergence of Python programming, digital forensics, and legal standards, offering a comprehensive framework for practitioners to navigate the complexities of digital investigations while ensuring the integrity of evidence under the Daubert Standard