This paper introduces a framework that combines machine learning for multi-class attack detection in IoT/IIoT networks with large language models (LLMs) for attack behavior analysis and mitigation suggestion. The framework uses role-play prompt engineering with RAG to guide LLMs like ChatGPT-o3 and DeepSeek-R1, and introduces new evaluation metrics for quantitative assessment. Experiments using Edge-IIoTset and CICIoT2023 datasets showed Random Forest as the best detection model and ChatGPT-o3 outperforming DeepSeek-R1 in attack analysis and mitigation.
KAUST researchers developed a hybrid wireless communication system for non-invasive monitoring of marine animals, consisting of a lightweight, flexible, Bluetooth-enabled tag that stores sensor data underwater. The tag syncs data to floating receivers when the animal surfaces, which then relays the data via GSM or drones. The system is a collaboration between the Red Sea Research Center and KAUST's electrical engineering department. Why it matters: This technology provides researchers with detailed, near real-time data about marine animals, overcoming the limitations of invasive and impractical traditional tagging methods.
A talk at the Directed Energy Research Center (DERC) at TII will discuss rapid prototyping using laser-cutting facilities available at MakerSpace in Al Zeina. The talk will cover constructing prototypes from wood and acrylic and compare this approach to traditional 3D printing. The speakers will also describe the impact of the ‘4th Industrial Revolution’ on manufacturing in the UAE, and how makerspaces can contribute to Operation 300bn. Why it matters: This highlights the UAE's focus on advanced manufacturing and the role of makerspaces in fostering innovation and developing local capabilities.
The Secure Systems Research Center (SSRC) won the Best Paper Award at EWSN 2023 for "BLoB: Beating-based Localization for Single-antenna BLE Devices," which introduces a method using concurrent transmissions to localize Bluetooth tags accurately. The system achieves sub-meter accuracy in indoor environments by having multiple anchors transmit simultaneously. A second SSRC paper, "InSight: Enabling NLOS Classification...", was also a runner-up in the Best Paper category. Why it matters: This award highlights the growing research capabilities in IoT and localization technologies within the GCC region, particularly for indoor environments where GPS is unavailable.
KAUST hosted the KAUST Sensor Initiative, convening experts in sensor development, material science, energy, communications, and data analysis. Live demonstrations showcased working prototypes, including a flexible sensor for monitoring the speed of dolphins developed by KAUST Ph.D. student Altynay Kaidarova. The initiative aims to advance a network of smarter, interactive physical IoT devices with embedded intelligent sensor technologies. Why it matters: This initiative highlights KAUST's role in fostering innovation in sensor technology and IoT, crucial for advancing smart infrastructure and environmental monitoring in the region.
KAUST researchers are exploring thin-film device technologies using materials like printable organics and metal oxides for a greener Internet of Things (IoT). They propose wirelessly powered sensor nodes using energy harvesters to reduce reliance on batteries, which are costly and environmentally harmful. Large-area electronics, printed on flexible substrates, offer a more eco-friendly alternative to silicon-based technologies due to solution-based processing and lower production temperatures. Why it matters: This research contributes to a more sustainable and environmentally friendly IoT ecosystem, aligning with global efforts to reduce electronic waste and energy consumption.
MBZUAI is hosting a talk by Professor Eric Xing on the challenges of moving from performance-oriented AI to production and industrial AI. The talk will cover theoretical foundations for panoramic learning, compositional strategies for building Pan-ML programs, optimization methods for tuning systems, and systems frameworks for scaling ML production. Professor Xing was previously a professor at Carnegie Mellon University and the founder of Petuum Inc. Why it matters: Bridging the gap between academic AI and real-world industrial applications is critical for unlocking the economic potential of AI in the UAE and beyond.