“Driving Tomorrow’s Innovations Today: Constructing a Secure and Smarter Digital World”
Our comprehensive suite of professional Researchers caters to a diverse areas of expertise.
AI and ML for Cybersecurity:
AI and ML for Cybersecurity: In our commitment to make digital spaces safer for everyone, our research is the intersection of theoretical computer science, AI, and ML to predict, detect, and mitigate cyber threats. From developing advanced algorithms for real-time threat detection to AI-powered incident response systems, we’re redefining cybersecurity standards.
Blockchain and Smart contracts for Security and Privacy:
In our blockchain research, we focus on using blockchain for secure authentication and access control, automating security protocols with smart contracts, and enabling privacy-preserving collaborative AI through blockchain-based federated learning. These initiatives aim to safeguard data integrity, ensure user privacy, and facilitate secure AI collaboration, marking significant strides towards a more secure digital future for all.
Smart Decentralized and Distributed Systems:
Our work aims at enhancing everyday life through intelligent technology. From smart home devices to urban infrastructure, our research emphasizes sustainability, user-friendliness, and automation. By incorporating AI and blockchain, we create systems that predict needs and enhance efficiency. Importantly, we’re also focused on evaluating AI and blockchain frameworks in these environments to ensure they’re effective and reliable for everyone’s use.
Computational Design Science
Our research focuses on the seamless integration of design principles with computational power, particularly through AI and ML. We aim to develop novel IT artifacts (e.g., models, techniques, and systems) to address practical needs of Information System (IS) research. To ensure these innovations are truly impactful, we conduct human experiments and conduct thorough benchmark evaluations against current state-of-the-art methods.
Federated Learning
Our research is exploring various federated learning operational modes- such as synchronous, asynchronous, and semi-asynchronous as a pioneering approach to build more private, secure, and efficient AI systems. By enabling devices to learn collaboratively while keeping data localized, we aim to advance AI research in a way that respects user privacy and reduces data centralization risks. This focus not only enhances AI models through diverse, real-world data but also paves the way for innovative applications across various sectors.
Software Vulnerability Detection
Our research is focused on making digital environments safer by finding and fixing software vulnerabilities. We use the latest AI and ML technologies to create tools that can quickly spot security issues in software systems. This helps us improve the security and reliability of these systems, protecting users from potential cyber threats and creating a more secure online experience for everyone.
Aim Of The LAB:
Our lab is dedicated to pioneering advancements in digital safety, privacy, and efficiency through advanced research in AI, ML, blockchain, and computational design. We focus on turning theoretical knowledge into practical solutions to meet the challenges in cybersecurity, smart decentralized systems, design science, and software integrity. Our goal is to build a safer, more intelligent, and user-friendly digital future for communities around the globe.