Here are some potential final project topics in Computer Engineering that focus on integrating undetectable AI technologies, ensuring these adhere to ethical guidelines and regulations:
1. Steganography with AI for Secure Communication
Develop an AI model that embeds and extracts hidden information (e.g., text or images) in digital media like audio, video, or images. Focus on making the embedded information undetectable to traditional detection tools.
2. AI-Powered Side-Channel Attack Detection and Prevention
Build an AI system that learns patterns from side-channel attacks (e.g., power usage or electromagnetic signals) to make encryption systems resistant to undetectable data breaches.
3. Smart Malware Detection and Evasion Techniques
Research AI models that analyze malware behaviors and develop countermeasures to avoid detection by conventional antivirus systems. Ensure ethical frameworks are incorporated to prevent misuse.
4. Privacy-Preserving Machine Learning Models
Create a federated learning model that processes data locally without transferring it to a central server. This ensures user privacy while making the AI’s operations effectively undetectable to external entities.
5. AI for Anonymous Traffic Routing in Networks
Develop an AI-powered system that optimizes Tor-like network routing for faster speeds and enhanced undetectability, ensuring anonymous and secure communication.
6. Deepfake Detection and Generation Arms Race
Explore an AI system to create undetectable deepfakes while simultaneously developing countermeasures for detecting the same. Emphasize ethical considerations.
7. AI-Driven Invisible CAPTCHA Breaker
Design an AI system capable of bypassing CAPTCHA systems using minimal detectable activity while ensuring its ethical use in legitimate automation.
8. AI in Digital Watermarking
Develop an undetectable AI-based digital watermarking technique that embeds copyright information in media files without compromising their quality or raising detection alarms.
9. AI for Low-Power IoT Security
Build an undetectable intrusion detection system for IoT devices that uses AI to analyze behavior patterns without increasing the device’s power consumption significantly.
10. Covert Neural Networks in Edge Devices
Design lightweight AI models that execute complex tasks on edge devices without revealing their presence or increasing power/resource usage noticeably.
Important Notes:
- Ethics First: Ensure your project has clear boundaries to prevent potential misuse.
- Documentation: Include detailed documentation to address the societal and ethical implications.
- Regulatory Compliance: Stay within the bounds of legal frameworks governing AI technologies.
Let me know if you’d like to expand on any of these topics!
