Blockchain and Machine Learning Based Detection system

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  Hack Days@DSU

In a world where digital payments were growing faster than security systems, companies struggled to stop clever fraudsters who kept finding new ways to attack. Traditional tools failed because they were slow, centralized, and easy to manipulate. To solve this, a team of students built a system combining blockchain and machine learning. The ML model learned patterns of fraudulent transactions, while the blockchain stored every result permanently and transparently. With PBFT consensus and smart contracts, no one could tamper with the data. This system detected fraud in real time, protected users, and restored trust in digital transactions.

Built With

• numpy
• pandas
• pbft-consensus-mechanism
• python
• scikitlearn