SRIG 24-83: Multi-Modal AI Approaches in Cybersecurity

What was the issue being addressed?

The issue addressed by this research project was the increasing limitations of traditional cybersecurity systems in responding to today’s modern and complex cyber threats. As cyberattacks become more advanced, have a larger scale, and faster speed, older conventional security mechanisms that rely on static, rule-based defenses are struggling in detecting and mitigating new and evolving threats. There is an increasing need for cybersecurity solutions that could adapt dynamically, detect complex attack patterns, respond in real time, and maintain transparency in decision-making. This project was established to address this rising gap by developing a multi-modal artificial intelligence (AI) framework that integrates machine learning (ML), deep learning (DL), reinforcement learning (RL), and expert systems into unified architecture. The objective was to build a system that would offer improved adaptability, accuracy, and interpretability in protecting systems against cyber threats. 

Provide a brief, lay description of the work undertaken/initiative.

This project aimed on creating an intelligent and robust cybersecurity system that will protect computers and networks from the increasing and complex online threats. Traditional security methods often lack speed and adaptability to stop new types of attacks. To overcome this, we designed a system that combines various types of artificial intelligence (AI) technologies together, such as machine learning, deep learning, reinforcement learning, and expert systems. Each component contributes a different role, allowing the system to quickly detect problems, learn and adapt to new attacks, and explain its decisions to human users. The main objective was to build a defense system that is not only responsive and accurate but also transparent and easy for cybersecurity teams to understand and monitor.

What is the expected impact this project will have on the community?

This project was designed to enhance the overall safety and resilience of digital systems used by individuals, businesses, and public institutions. Creating a cybersecurity system that can detect and respond to greater speed and precision threats, we aim to reduce the risk of cyberattacks that can compromise sensitive information, disrupt essential services, or cause financial losses. Additionally, this project also helps in building public trust in digital technologies by encouraging and enhancing transparency and accountability in cybersecurity decisions making. Over time, the research could contribute to shaping smarter, more adaptive cybersecurity tools that are accessible to large organizations as well as smaller businesses and communities with limited advanced technical resources. Ultimately, this will support a safer, more secure digital environment for everyone.