Visual Cryptograpgy (Image Encryption and Decryption)

An image encryption tool using visual cryptography. The secret image is split into shares that look like random noise; overlaying the right shares reveals it.

Users connect a wallet such as MetaMask to the web front end. Each record (for example a product batch, certificate or vote) is written by a Solidity smart contract on an Ethereum test network. The contract checks who is allowed to add or update data, so only authorised accounts can write. Anyone with the record ID can verify its full history, which cannot be edited afterwards.

Records on a blockchain are shared across nodes, linked by cryptographic hashes and cannot be altered without consensus. This gives tamper-proof history and removes the need to trust one central administrator.

A program stored on the blockchain that runs automatically when its conditions are met. In Ethereum it is written in Solidity, compiled to bytecode and executed by every node, so its result cannot be changed by one party.

Capture the frame, convert to grayscale, remove noise with a Gaussian blur, segment the region of interest with thresholding or edge detection, extract features and finally classify or match them.

First a detector (Haar cascade, HOG or a CNN) finds the face. Then a model converts it into an embedding, a list of numbers that describes the face, and compares it with stored embeddings using a distance measure.

Symmetric encryption (AES, DES) uses one shared key for encryption and decryption and is fast. Asymmetric encryption (RSA) uses a public key to encrypt and a private key to decrypt, which solves key sharing but is slower.

We followed an iterative (incremental) model: requirements and a basic design first, then modules built and tested one by one, with the guide's feedback after each review. It suits a project where requirements become clearer as we build.

Unit testing of each module, integration testing of the complete flow and system testing with real inputs. Test cases with expected and actual results are listed in the report, including invalid inputs.

The current version is tested on a limited dataset or number of users. Future work includes deploying on the cloud, adding more features or languages, improving accuracy with more data and building a mobile version.