Forensic analysis of video data deletion and recovery in Honeywell surveillance file system

• URL: http://arxiv.org/abs/2605.07430v1
• Date: Fri, 08 May 2026 08:31:12 GMT
• Title: Forensic analysis of video data deletion and recovery in Honeywell surveillance file system
• Abstract summary: Real-time video surveillance systems store recorded video using digital video recorders (DVRs) and network video recorders (NVRs)<n>These devices employ specialized, nonstandard file systems that are often proprietary and undocumented.<n>We analyze an undocumented proprietary file system used by Honeywell video surveillance devices.
• Score: 3.81006880749861
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Real-time video surveillance systems store recorded video using digital video recorders (DVRs) and network video recorders (NVRs). To support continuous high-volume video storage, these devices employ specialized, nonstandard file systems that are often proprietary and undocumented. This lack of documentation significantly increases the time and effort required for forensic analysis. In this study, we analyze an undocumented proprietary file system used by Honeywell video surveillance devices-one that, to the best of our knowledge, has not been examined in prior work-and investigate its deletion mechanisms and demonstrate the feasibility of video recovery after deletion. We perform a file system analysis using a binary diffing technique and evaluate three deletion methods supported by the target device: 1) formatting-based deletion, 2) data expiration, and 3) overwrite. For each method, we investigate changes in file system metadata and on-disk data structures and demonstrate the feasibility of video data recovery. Our findings aim to support more efficient and accurate forensic investigations of Honeywell surveillance products and provide foundational insights into the analysis of proprietary file systems used in video recording devices.

Related papers

• Learning Unified Video and Image Representation for Video Face Forgery Detection [49.19035628283472]
  Existing methods for video face forgery detection assume that all frames in a forged video are manipulated.<n>We propose a novel framework, UVIF, that utilizes additional annotated images to provide fine-grained supervision for detecting partial forgeries in videos.<n>UVIF employs a unified encoder and a multi-task learning paradigm to jointly model facial videos and images for boosted video face forgery detection.
  arXiv  Detail & Related papers  (2026-08-13T10:25:59Z)
• Video Forgery Detection for Surveillance Cameras: A Review [4.384167706308244]
  Surveillance footage plays a crucial role in security, law enforcement, and judicial processes.<n>With the rise of advanced video editing tools, tampering with digital recordings has become increasingly easy.<n> Ensuring the integrity of surveillance videos is essential, as manipulated footage can lead to misinformation and undermine judicial decisions.
  arXiv  Detail & Related papers  (2025-05-04T12:21:24Z)
• VideoRepair: Improving Text-to-Video Generation via Misalignment Evaluation and Localized Refinement [63.4357918830628]
  VideoRepair is a model-agnostic, training-free video refinement framework.<n>It identifies fine-grained text-video misalignments and generates explicit spatial and textual feedback.<n>VideoRepair substantially outperforms recent baselines across various text-video alignment metrics.
  arXiv  Detail & Related papers  (2024-11-22T18:31:47Z)
• Restoration of Analog Videos Using Swin-UNet [28.773037051085318]
  We present a system to restore analog videos of historical archives. The proposed system uses a multi-frame approach and is able to deal with severe tape mistracking.
  arXiv  Detail & Related papers  (2023-11-07T16:00:31Z)
• UVL2: A Unified Framework for Video Tampering Localization [0.0]
  Malicious video tampering can lead to public misunderstanding, property losses, and legal disputes. This paper proposes an effective video tampering localization network that significantly improves the detection performance of video inpainting and splicing.
  arXiv  Detail & Related papers  (2023-09-28T03:13:09Z)
• Forensic Video Analytic Software [1.55172825097051]
  Law enforcement officials heavily depend on Forensic Video Analytic (FVA) Software in their evidence extraction process. The term forensic pertains the application of scientific methods to the investigation of crime through post-processing, whereas surveillance is the close monitoring of real-time feeds. This project has resulted in three research outcomes Moving Object Based Collision Free Video Synopsis, Forensic and Surveillance Analytic Tool Architecture and Tampering Detection Inter-Frame Forgery.
  arXiv  Detail & Related papers  (2023-09-17T18:02:43Z)
• Ensembling object detectors for image and video data analysis [98.26061123111647]
  We propose a method for ensembling the outputs of multiple object detectors for improving detection performance and precision of bounding boxes on image data. We extend it to video data by proposing a two-stage tracking-based scheme for detection refinement.
  arXiv  Detail & Related papers  (2021-02-09T12:38:16Z)
• Efficient video integrity analysis through container characterization [77.45740041478743]
  We introduce a container-based method to identify the software used to perform a video manipulation. The proposed method is both efficient and effective and can also provide a simple explanation for its decisions. It achieves an accuracy of 97.6% in distinguishing pristine from tampered videos and classifying the editing software.
  arXiv  Detail & Related papers  (2021-01-26T14:13:39Z)
• A Modified Fourier-Mellin Approach for Source Device Identification on Stabilized Videos [72.40789387139063]
  multimedia forensic tools usually exploit characteristic noise traces left by the camera sensor on the acquired frames. This analysis requires that the noise pattern characterizing the camera and the noise pattern extracted from video frames under analysis are geometrically aligned. We propose to overcome this limitation by searching scaling and rotation parameters in the frequency domain.
  arXiv  Detail & Related papers  (2020-05-20T12:06:40Z)
• Multi-Modal Video Forensic Platform for Investigating Post-Terrorist Attack Scenarios [55.82693757287532]
  Large scale Video Analytic Platforms (VAP) assist law enforcement agencies (LEA) in identifying suspects and securing evidence. We present a video analytic platform that integrates visual and audio analytic modules and fuses information from surveillance cameras and video uploads from eyewitnesses.
  arXiv  Detail & Related papers  (2020-04-02T14:29:27Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.