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https://github.com/saro0307/tavern-cut
Tavern cut is a Turing test integrated Encryption system that provides additional layer of protect for web servers against Malware bots.
https://github.com/saro0307/tavern-cut
artificial-intelligence cybersecurity encryption jypyternotebook machine-learning machine-learning-algorithms python python3 research research-paper research-project smtplib tkinter tkinter-python turing-machine turing-test
Last synced: 8 days ago
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Tavern cut is a Turing test integrated Encryption system that provides additional layer of protect for web servers against Malware bots.
- Host: GitHub
- URL: https://github.com/saro0307/tavern-cut
- Owner: saro0307
- License: apache-2.0
- Created: 2024-06-12T12:54:30.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-07-05T14:51:37.000Z (7 months ago)
- Last Synced: 2024-11-13T19:14:28.968Z (2 months ago)
- Topics: artificial-intelligence, cybersecurity, encryption, jypyternotebook, machine-learning, machine-learning-algorithms, python, python3, research, research-paper, research-project, smtplib, tkinter, tkinter-python, turing-machine, turing-test
- Language: Python
- Homepage:
- Size: 535 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Tavern-cut
Tavern Cut is an advanced cybersecurity application that integrates a Turing Test algorithm with artificial intelligence (AI) to enhance password protection and fortify online accounts against unauthorized access. This project aims to provide a robust and adaptive security mechanism by distinguishing between legitimate users and potential intruders through human-like conversational interactions.
## Features
- **AI-Driven Turing Test:** Utilizes AI to engage users in dynamic conversations during login attempts to assess authenticity.
- **Intruder Alert Mechanism:** Sends automated email alerts to notify users of potential unauthorized access attempts.
- **Continuous Learning:** The system evolves over time, improving its ability to distinguish between genuine users and threats through machine learning.
- **User-Friendly Interface:** Provides a seamless and intuitive interface for user registration, login, and response to security alerts.
## Installation
1. **Clone the repository:**
```sh
git clone https://github.com/saro0307/tavern-cut.git
cd tavern-cut
```
2. **Install required libraries:**
```sh
pip install -r requirements.txt
```
3. **Configure email settings:**
Replace the placeholders in the code with your actual email credentials:
```python
email_sender = '[email protected]'
email_password = 'your_password'
email_receiver = '[email protected]'
```
4. **Run the application:**
```sh
python tavern_cut.py
```
## Usage
1. **User Registration:**
- Enter your email address and set up a secure password.
2. **Login:**
- Enter your username and password.
- The system will engage in a human-like conversation to verify authenticity.
3. **Security Alerts:**
- In case of unauthorized access attempts, an email alert will be sent to the configured email address.
## Code Overview
### Turing Machine States and Transitions
The Turing machine is implemented to verify the password correctness through a series of states and transitions.
```python
states = {
"q0": {"r": ("q1", "r", "R")},
"q1": {"u": ("q2", "u", "R")},
"q2": {"s": ("q3", "s", "R")},
"q3": {"s": ("accept", "s", "S")},
"q4": {"i": ("accept", "i", "S")},
"q5": {"a": ("accept", "a", "S")},
}
```
### Email Alert Configuration
The `send_email_alert` function sends an email notification if an unauthorized login attempt is detected.
```python
def send_email_alert():
# Email configuration and sending logic
```
### GUI Setup
The application uses Tkinter to create a user-friendly interface for login and registration.
```python
root = tk.Tk()
root.title("Login Page")
# GUI components setup
root.mainloop()
```
## Future Work
Future evaluations will focus on:
- **Scalability:** Assessing system performance under increased user load.
- **Real-World Deployment:** Testing the system in corporate networks and large-scale platforms.
- **Adaptability:** Enhancing resilience against sophisticated AI-driven attacks.
- **User Experience:** Continuously improving the user interface and reducing false positives.
- **Cross-Platform Compatibility:** Ensuring seamless performance across various operating systems, browsers, and devices.
- **Legal Compliance:** Ensuring adherence to privacy regulations and data protection laws.
## Conclusion
Tavern Cut represents a significant advancement in cybersecurity, integrating the Turing Test algorithm with AI to provide a dynamic and adaptive defense mechanism. This project demonstrates the potential of AI in enhancing online security, offering a robust solution against evolving cyber threats.
## Authors
- Sam Priesly Mathuram P
- Saravana Kumar G
- Sudharsun B
- Thiru Vigneswaran babu S
## License
This project is licensed under the Apache-2.0 license. See the [LICENSE](LICENSE) file for details.
## Acknowledgments
- SNS College of Engineering, Coimbatore, Tamil Nadu, India
- All contributors and supporters of the project
For more details, refer to the project report available [here](https://ijsart.com/Home/IssueDetail/90871) (Volume 10 Issue 5 – MAY 2024).