The Internet serves as a conduit for vast amounts of sensitive data, making it a prime target for cyber threats. Attacks like Distributed Denial-of-Service (DDoS), prefix hijacking, and traffic interception can degrade services and compromise user privacy. At the global level, disruptive events such as large-scale power outages, undersea cable cuts, or Internet worms, can cause “Internet earthquakes,” making the Internet deviate from its normal state of operation. Our research delves into innovative detection and mitigation strategies. By harnessing the latest advancements in machine learning and network monitoring, we aim to develop comprehensive solutions that bolster Internet security, safeguard user privacy, and enhance trust in online environments.

The proliferation of Internet of Things (IoT) devices and mobile technologies has transformed how we interact with our environments, including smart healthcare, smart home, smart grid, smart vehicle, and smart cities. While the number, complexity, and functions of IoT and mobile devices have been growing, these interconnected devices often operate with limited security features, making them vulnerable to a range of threats, including unauthorized access and data breaches. Our research investigates secure protocols and privacy-enhanced service discovery methods. By employing cutting-edge techniques from cryptography and adaptive security mechanisms, we strive to create resilient frameworks that protect sensitive data while enabling seamless user experiences. The goal is to promote secure and trustworthy interactions in an increasingly connected world.

Blockchain technology has emerged as a transformative solution for enhancing data security and privacy across diverse applications, including in the realms of Decentralized Finance (DeFi) and cryptocurrency. Its decentralized architecture ensures secure transactions and robust data integrity, yet challenges such as scalability and privacy management persist. We study innovative solutions like privacy-preserving attribute-based credentials and accountable rewriting techniques, which enable flexible data modifications without compromising security. We also explore the implications of smart contracts and tokenization. By addressing the fundamental challenges, we aim to promote secure, efficient, and user-friendly blockchain applications in the evolving digital economy.

As Artificial Intelligence (AI) permeates various sectors—from healthcare to finance, it demands robust frameworks that ensure high system performance while facilitating the seamless training, deployment, serving, and maintenance of AI models. This entails advancements in not only distributed machine learning and generative AI, but also computing and communication infrastructures and systems. Effective AI systems should leverage cloud datacenter environments for scalable processing and harness edge computing for timely insights, while striving to provision AI accuracy and quality. Our research explores the synergies between AI and these foundational and supportive technologies, aiming to enhance efficiency, agility, resilience, and accuracy while promoting responsible innovation in AI-driven solutions.