Authenticity for Digital Evidence in CCTV Recordings through Simulation Based
In many criminal cases, CCTV footage plays a crucial role as a form of digital evidence in the courtroom. However, one can question the veracity of these videos due to the potential for these clips to be altered. Therefore, the integrity and authenticity of the video footage acquired must be obtained and preserved with extra caution. The Generic Computer Forensic Investigation Model (GCFIM) provides a robust framework for detecting CCTV tampering and validating digital evidence authenticity. This research method involves the use of genuine and counterfeit CCTV footage with varying resolutions as part of the investigation. Supporting tools such as MediaInfo, Forevid, ExifTool, Amped Five, and Video Metadata Comparator were used to analyze the data. This research was conducted using structured and standardized procedures in accordance with GCFIM. The results of the study confirmed that GCFIM is very effective at detecting manipulations in CCTV footage, with 96.8% accuracy based on an analysis of the frame, bitrate, and time stamp metadata. This model also provides consistent results despite variations in recording quality. The higher the resolution of the footage, the easier and more accurate the analysis. This study contributes by bridging the gap between theoretical forensic frameworks and practical implementation, enhancing the credibility of digital evidence and supporting its admissibility in legal proceedings
Authors:
Andrea Stevens Karnyoto, Bens Pardamean, Indo Intan, Asmah Akhriana, Nurdin, Aryandi, Nades Kola Samperuru, Bayou Tilahun Assaye, Yihenew Alemu Haile
International Conference on Smart Computing, IoT, and Machine Learning (SIML 2026)