Blockchain Based Personal Identity Security System

A system that stores personal identity documents securely using blockchain. Users upload documents, the admin verifies them, and the verified records are hashed onto the chain so they cannot be forged or changed.

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.

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.

A hash is one-way, so even the administrator cannot recover the password. We add a random salt and use a slow hash such as bcrypt so stolen hashes are hard to crack.

Web Forms uses server controls and view state with an event model. MVC separates Model, View and Controller, gives full control over HTML and is easier to test.

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.