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Block Chain/ Cyber Security


Introduction : Projects focused on secure transactions, data protection, or decentralized systems.


Projects :

    Project Title : Secure Notepad (C)

    Statement : Encrypt and store sensitive notes.

    Approach : Used AES encryption with password hashing.

    Tools : C, OpenSSL library.


      Project Title : Cryptocurrency Wallet

      Project Statement : Build a secure wallet for managing cryptocurrencies.

      Approach : Use cryptographic techniques to ensure secure transactions.

      Tools & Technology : Python, Solidity, Web3.py, Metamask.


        Project Title : Smart Contract Auditor

        Project Statement : Audit smart contracts for vulnerabilities.

        Approach : Use static analysis and formal verification.

        Tools & Technology : Solidity, Mythril, Slither, Ganache.


          Project Title : Decentralized Voting System

          Project Statement : Create a transparent and secure voting platform.

          Approach : Use blockchain to ensure vote integrity and anonymity.

          Tools & Technology : Ethereum, Solidity, Web3.js, React.


            Project Title : Credit Card Fraud Detection

            Statement : Identify fraudulent transactions in real time.

            Approach : Trained anomaly detection models on transaction data.

            Tools : Python (Scikit-learn), PostgreSQL.


              Project Title : Blockchain Energy Consumption Tracker

              Statement : Monitor energy usage on a decentralized ledger.

              Approach : Built with Ethereum smart contracts for transparency.

              Tools : Solidity, Truffle, MetaMask.


                Project Title : Data Spark Cybersecurity Tool

                Statement : Detect and mitigate cyber threats in networks.

                Approach : Analyzed logs and traffic patterns with ML.

                Tools : Python, Snort IDS, TensorFlow.


                  Project Title : AI-Driven Phishing Detection

                  Statement : Block phishing emails using NLP.

                  Approach : Trained models on email content and metadata.

                  Tools : Python, TensorFlow, AWS Lambda.