SecureMed Connect is a secure Client-Server application designed for confidential medical consultations. Unlike standard chatbots, this system prioritizes data privacy by establishing an Encrypted SSL/TLS Channel between the doctor (Server) and the patient (Client).

The application is built using raw Python Sockets to demonstrate a deep understanding of network protocols, multi-threading, and secure communication standards required in the healthcare industry (HIPAA compliance simulation).

• Secure Communication (SSL/TLS):
  • Uses ssl module to wrap standard TCP sockets.
  • Implements Public Key Infrastructure (PKI) using Self-Signed Certificates.
  • Ensures end-to-end encryption to prevent Man-in-the-Middle (MITM) attacks.
• Client-Server Architecture:
  • Multi-threaded Server: Handles multiple patients simultaneously using Python threading.
  • Stateful Connections: Maintains session context for each connected client.
• Authentication & Integrity:
  • Server authenticates using a customized Root CA certificate.
  • Verifies data integrity during transmission.
• Interactive GUI:
  • User-friendly interface built with PyQt5 (.ui files integrated).

• Language: Python 3.x
• Networking: Socket Programming (TCP/IP), SSL/TLS Context.
• Concurrency: Threading.
• GUI: PyQt5.
• Data: JSON (Lightweight medical knowledge base).

git clone [https://github.com/mariamashraf731/SecureMed-Connect.git](https://github.com/mariamashraf731/SecureMed-Connect.git)

Since private keys are sensitive, they are not included in the repo. You must generate them:

# Generate Root Key
openssl genrsa -out RootCA.key 2048
# Generate Root Certificate
openssl req -x509 -new -nodes -key RootCA.key -sha256 -days 1024 -out RootCA.pem
# Place these files in the 'certs/' directory

Start the Server first:

python src/server/server.py

Start a Client (Patient):

python src/client/main.py

• src/server: Handles encrypted connections and queries the medical database.
• src/client: GUI application for patients to interact securely.
• data: Contains medical_db.json with symptom-disease mappings.