Development of a Multi-Vendor DVR/NVR Forensic Analysis Tool for Standardized Acquisition, Recovery, and Analysis of Surveillance Evidence.

• Background Digital/Network Video Recorders (DVR/NVRs) are widely used for surveillance in government agencies, law enforcement, critical infrastructure, businesses, and residential environments. Major DVR/NVR manufacturers such as Dahua Technology, CP Plus, Honeywell Security, TP-Link, Godrej, Uniview, HIKVISON, and Matrix use proprietary storage formats, file systems, metadata structures, and video encoding mechanisms. During forensic investigations, surveillance footage serves as crucial digital evidence; however, the lack of standardization across DVR/NVR vendors makes acquisition, recovery, analysis, and validation difficult. Investigators often rely on multiple vendor-specific tools, resulting in increased investigation time, inconsistent results, timestamp synchronization issues, challenges in deleted footage recovery, and difficulties in maintaining evidence integrity. Therefore, a unified vendor-agnostic DVR/NVR forensic analysis platform is required to provide standardized workflows for evidence acquisition, recovery, analysis, validation, and reporting. • Description The proposed solution aims to overcome challenges such as non-standard forensic acquisition methods, proprietary file systems and video formats, difficulty in recovering deleted or damaged recordings, inconsistent timestamps, limited event correlation across cameras, challenges in maintaining chain of custody, dependence on multiple tools, lack of standardized reporting, and limited use of intelligent video analytics. The tool should support major DVR/NVR OEMs including Dahua Technology, CP Plus, Honeywell Security, HIKVISON, TP-Link, Godrej, Uniview, Matrix, and other commonly used platforms. It should automatically identify DVR models, parse proprietary file systems, create forensic images, extract videos and metadata, decode proprietary formats, recover deleted footage, normalize timestamps, generate cryptographic hashes (MD5 and SHA-256), correlate events across cameras, maintain chain-of-custody records, generate reports, and perform AI-based analytics such as face, object, and motion detection. Key modules include Device Identification, Acquisition, File System & Format Parsing, Recovery, Timeline Analysis, Reporting, and Machine Learning. • Expected Solution The expected outcome is a software-based forensic platform capable of performing standardized acquisition, recovery, analysis, validation, and reporting of surveillance evidence across multiple DVR/NVR vendors. The solution should support at least five to six major DVR/NVR OEMs (Dahua Technology, CP Plus, Honeywell Security, TP-Link, Godrej, Uniview, HIKVISON and Matrix), provide a unified forensic workflow, reduce dependency on vendor-specific tools, automate evidence acquisition and analysis, improve deleted video recovery, ensure evidence integrity and admissibility, and generate comprehensive forensic reports. Deliverables include a comparative analysis of major DVR/NVR OEMs (Dahua Technology, CP Plus, Honeywell Security, TP-Link, Godrej, Uniview, and Matrix), DVR/NVR forensic Image, system architecture documentation, a functional prototype, Standard Operating Procedures (SOPs), validation reports, user manuals, and a final project report. The tool should successfully parse proprietary file systems, decode video formats, recover deleted recordings,verify evidence integrity through cryptographic hashing, generate standardized reports, reduce analysis time, and produce reliable and legally defensible forensic results.