SIH26188/Blockchain & Cybersecurity

AI border security identity screening system

An AI-powered document screening platform for border security personnel that extracts text, validates documents, detects tampering, and verifies faces.

Ministry of Home Affairs · Sashastra Seema Bal (SSB), Police II Division · Software

Teams already in: 3/500almost everyone who enters · read 1 hour ago
Buildable in 36 hours: ModerateOur estimate, from their wording
Hard blockers: NoneNothing you must source first
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 10 problem statement(s) in SIH 2025. It has awarded 4 joint winner(s), so it sometimes splits a prize between two teams.

What you would have to build

Decomposed from what the description asks for. Nothing added.

01
OCR Extraction Module
Automatically extract information from passports, visas, national IDs, driving licenses, and permits.
02
Document Validation Module
Verify whether the extracted information follows official document standards.
03
Tampering Detection Module
Detect digitally or physically altered documents including photo replacements, text manipulation, and forged stamps.
04
Face Verification Module
Ensure the document owner matches the presented individual.

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 accurately extracts text, detects various types of document tampering, and successfully matches faces to verify identity.

They never say

specific databases to integrate with for validation
exact risk scoring formula or thresholds

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 databases to integrate with for validation?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Exact risk scoring formula or thresholds?
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.

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

The brief asks for ocr extraction module. How would you build that?
Decoded from SIH26188 itself — Automatically extract information from passports, visas, national IDs, driving licenses, and permits. The brief asks for it by name.

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 Ministry of Home Affairs

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 SIH26188, set by Ministry of Home Affairs.
Its official title, word for word: "Al-Based Fake Identity & Document Screening System"
Theme: Blockchain & Cybersecurity. Category: software.

In plain terms: An AI-powered document screening platform for border security personnel that extracts text, validates documents, detects tampering, and verifies faces.

## The organisers' full description, verbatim

• Background Common challenges faced at border checkpoints: • Fake passports and visas • Altered photographs • Modified dates of birth • Tampered visa stamps • Identity impersonation • Multiple identities used by the same person Expired or blacklisted travel documents • High passenger volume causing delays Current verification methods rely heavily on human inspection and basic database lookups. • Detailed Description Border checkpoints process thousands of identity documents every day,including passports, visas, national identity cards, permits, and travel authorizations. Manual verification is time-consuming, prone to human error, and often unable to detect sophisticated forgeries, tampering, or identity fraud.Develop an Al-powered document screening platform that automatically analyzes identity and travel documents, detects signs of tampering or forgery, validates information against rules and databases,and generates a risk score to assist border security personnel in making faster and more accurate decisions. • Expected Solution • Module 1: OCR Extraction • Module 2: Document Validation • Module 3: Tampering Detection • Module 4: Face Detection Module 1: OCR Extraction Objective: Automatically extract all relevant information from identity documents. Inputs: • Passport image • Visa image • National ID image • Driving license • Permit documents Extracted Fields: Passport • Name • Passport Number • Nationality • Date of birth • Date of expiry • Gender Visa • Visa Number • Visa Type • Entry Validation • Stay Duration Module 2: Document Validation Objective: Verify whether the extracted information follows official document standards. Module 3: Tampering Detection (Core AI Innovation) Objective: Detect digitally or physically altered documents. Use Cases: • Photo Replacement • Text Manipulation • Stamp Forgery Detection • Image Metadata Analysis Module 4: Face Verification Objective: Ensure document owner matches the presented individual. • Expected Impact • Reduce document verification time from several minutes to a few seconds. • Improve detection of forged and tampered documents. • Standardize screening decisions across checkpoints. • Enable data-driven risk assessment instead of purely manual inspection. • Create a digital trail for investigations and intelligence analysis. Possible Project Name Al-Based Fake Identity & Document Screening System.

## What the brief never says

- specific databases to integrate with for validation
- exact risk scoring formula or thresholds
## 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.

## 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 Ministry of Home Affairs'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 (340 words)

• Background Common challenges faced at border checkpoints: • Fake passports and visas • Altered photographs • Modified dates of birth • Tampered visa stamps • Identity impersonation • Multiple identities used by the same person Expired or blacklisted travel documents • High passenger volume causing delays Current verification methods rely heavily on human inspection and basic database lookups. • Detailed Description Border checkpoints process thousands of identity documents every day,including passports, visas, national identity cards, permits, and travel authorizations. Manual verification is time-consuming, prone to human error, and often unable to detect sophisticated forgeries, tampering, or identity fraud.Develop an Al-powered document screening platform that automatically analyzes identity and travel documents, detects signs of tampering or forgery, validates information against rules and databases,and generates a risk score to assist border security personnel in making faster and more accurate decisions. • Expected Solution • Module 1: OCR Extraction • Module 2: Document Validation • Module 3: Tampering Detection • Module 4: Face Detection Module 1: OCR Extraction Objective: Automatically extract all relevant information from identity documents. Inputs: • Passport image • Visa image • National ID image • Driving license • Permit documents Extracted Fields: Passport • Name • Passport Number • Nationality • Date of birth • Date of expiry • Gender Visa • Visa Number • Visa Type • Entry Validation • Stay Duration Module 2: Document Validation Objective: Verify whether the extracted information follows official document standards. Module 3: Tampering Detection (Core AI Innovation) Objective: Detect digitally or physically altered documents. Use Cases: • Photo Replacement • Text Manipulation • Stamp Forgery Detection • Image Metadata Analysis Module 4: Face Verification Objective: Ensure document owner matches the presented individual. • Expected Impact • Reduce document verification time from several minutes to a few seconds. • Improve detection of forged and tampered documents. • Standardize screening decisions across checkpoints. • Enable data-driven risk assessment instead of purely manual inspection. • Create a digital trail for investigations and intelligence analysis. Possible Project Name Al-Based Fake Identity & Document Screening System.