We are a research group based in the School of Computer Science and Engineering, Nanyang Technological University. We focus on the research, design, and evaluation of networked, energy-efficient, and secure sensing systems found in the Internet of Things (IoT) and its AI-empowered generation (AIoT). Our research has two main sub-directions of IoT sensing systems/applications and security/privacy of AIoT sensing. In the first sub-direction, with a strong experimental focus, we study a number of sensing modalities (e.g., powerline radiation, radio frequency, acoustics, image, thermal, and energy), exploit them to construct system functions and applications. In the second sub-direction, we study the security and privacy of AIoT sensing systems that use machine learning to process the sensed data. Due to the immediate application potential, our research has been funded (or co-funded) externally by government authorities and companies in the ICT, energy, and manufacturing sectors.
Featured recent research
[IEEE ICDCS'20] Attack-Aware Data Timestamping in Low-Power Synchronization-Free LoRaWAN Maintaining tight clock synchronization of LoRaWAN end devices for data timestamping is costly due to limited bandwidth. We show that timestamping based on uplink frame arrival time at the gateway is efficient but can be insecure. We design a gateway added with the RTL-SDR to analyze the bias of the uplink carrier frequency to improve the security of gateway-side data timestamping.