SIH26150/Blockchain & Cybersecurity

Multi-vendor DVR surveillance forensics platform

A software forensic platform that lets law enforcement investigators acquire, recover, and analyze surveillance footage from multiple vendor DVR and NVR devices.

National Technical Research Organisation (NTRO) · Software

Teams already in: 1/500almost everyone who enters · read 1 hour ago
Buildable in 36 hours: LowOur estimate, from their wording
Hard blockers: 1Restricted data
Submissions close: 15 Sept9 days left

Make this one of our two Compare with others

Signing in saves it for your whole team — everyone on your invite link sees the same two entries. Anything you shortlisted while signed out comes with you.

Submit on sih.gov.in

Whether this suits your team

Why this fits you

This organisation declared winners on 13 problem statement(s) in SIH 2025 and on 13 in SIH 2024. It has awarded 4 joint winner(s), so it sometimes splits a prize between two teams.

What argues against it

Potential concern: needs data you may not get.

What you would have to build

Decomposed from what the description asks for. Nothing added.

01
Device Identification Module
Automatically identifies DVR and NVR models from major OEMs.
02
Acquisition and Parsing
Creates forensic images and parses proprietary file systems and video formats.
03
Recovery and Validation
Recovers deleted footage and generates MD5 and SHA-256 cryptographic hashes for evidence integrity.
04
Timeline and Analytics
Normalizes timestamps, correlates events across cameras, and runs AI-based object, face, and motion detection.
05
Reporting Module
Maintains chain of custody records and generates standardized forensic reports.

What they ask for, and what they leave open

Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.

They state

The jury will check whether your platform supports at least five to six specified OEMs like Dahua, CP Plus, and Hikvision, parses proprietary file systems, recovers deleted recordings, and ensures evidence integrity using MD5 and SHA-256 hashes.

They never say

specific sample forensic dump files from each named manufacturer
exact legal standards or court admissibility requirements for the target jurisdiction

A jury can still ask about these. Decide them deliberately rather than by accident.

What they'll ask you

Generated from the brief's own wording and the competition's published rules — never from a guess about what this ministry prefers.

Specific sample forensic dump files from each named manufacturer?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Exact legal standards or court admissibility requirements for the target jurisdiction?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Has any part of this been shown at a previous event, hackathon or college project?
The guidelines are explicit: your solution must not have appeared in any previous event or programme, of any sort. A recycled project is what a team under time pressure reaches for.

9 more— the ones a panel gets to if there is time

The brief asks for device identification module. How would you build that?
Decoded from SIH26150 itself — Automatically identifies DVR and NVR models from major OEMs. The brief asks for it by name.

Before you commit

Each one is quoted from a gap in the brief, not a guess about your team.

Needs data you may not get
The description requires parsing proprietary storage formats and file systems from major manufacturers like Dahua, Hikvision, and Honeywell which students cannot easily obtain.

The data

What the organisers attached, and what the brief assumes you can get.

Dataset from the organisers: None attached
Does the brief need data?: Nothing in the text says it depends on a dataset we would have to find.

Also from National Technical Research Organisation (NTRO)

Same organisation, same year. Reading two of theirs tells you more about what they care about than reading one.

Take this to an AI

Pick what you are about to do and copy the prompt. It carries the organisers' own wording, the constraints they never spell out, and an instruction not to invent requirements they never set.

Who has this problem, what already exists, and what you would have to find out.

# Context: India's Smart India Hackathon 2026

I am on a student team entering SIH 2026. Problem statement SIH26150, set by National Technical Research Organisation (NTRO).
Its official title, word for word: "Development of a Multi-Vendor DVR/NVR Forensic Analysis Tool for Standardized Acquisition, Recovery, and Analysis of Surveillance Evidence."
Theme: Blockchain & Cybersecurity. Category: software.

In plain terms: A software forensic platform that lets law enforcement investigators acquire, recover, and analyze surveillance footage from multiple vendor DVR and NVR devices.

## The organisers' full description, verbatim

• 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.

## What the brief never says

- specific sample forensic dump files from each named manufacturer
- exact legal standards or court admissibility requirements for the target jurisdiction
## Constraints that are not negotiable

- The judged build is a prototype demonstrated in roughly 36 hours by students, not a product.
- A jury evaluates it against this problem statement's own wording, not against general merit.
- We submit on sih.gov.in; the problem statement number and title above must match exactly.
- Your solution must not have appeared in any previous event or programme, of any sort.
- Known obstacles in the brief: Restricted data.

## What I want from you

1. Who actually has this problem in India, and what they do about it today.
2. What already exists — government systems, open-source projects, published research — that we should not rebuild.
3. For each item under 'what the brief never says', what the realistic answer is likely to be and how I could verify it.
4. The two or three things about this domain that a student team would get wrong without local knowledge.
## How to answer

- Everything above between quotation marks is the organisers' own wording. Treat it as the requirement.
- Do NOT invent requirements the brief does not state. If something matters and is not stated, say so and ask me, rather than assuming.
- Where you are inferring rather than reading, mark it as your inference.
- Do not guess what this ministry wants from its name. Its wording above is the only evidence.

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Problem statement facts assembled by Wynit from National Technical Research Organisation (NTRO)'s published brief for SIH 2026.
The plain-English summary, the list of parts and the evaluator read are our interpretation of that text; the quoted title and the full description are theirs.

The government's original description (431 words)

• 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.