Computer Science Research Works
Permanent URI for this collectionhttp://hdl.handle.net/1903/1593
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Item Structure Assisted Spectrum Sensing for Low-power Acoustic Event Detection(Association for Computer Machinery (ACM), 2023-05-09) Garg, Nakul; Takawale, Harshvardhan; Bai, Yang; Shahid, Irtaza; Roy, NirupamAcoustic sensing has conventionally been dependent on highfrequency sampling of analog signals and frequency domain analysis in digital domain which is power-hungry. While these techniques work well for regular devices, low-power acoustic sensors demand for an alternative approach. In this work, we propose Lyra, a novel low-power acoustic sensing architecture that employs carefully designed passive structures to filter incoming sound waves and extract their frequency components. We eliminate power-hungry components such as ADC and digital FFT operations and instead propose to use low-power analog circuitry to process the signals. Lyra aims to provide a low-power platform for a range of maintenance-free acoustic event monitoring and ambient computing applications.Item ThermWare: Toward Side-channel Defense for Tiny IoT Devices(Association for Computer Machinery (ACM), 2023-02-22) Garg, Nakul; Shahid, Irtaza; Avllazagaj, Erin; Hill, Jennie; Han, Jun; Roy, NirupamAs malware in IoT devices !ourishes, defenses are lacking. Traditional antivirus or intrusion detection-based defense techniques fail for the limited computational capabilities and the large diversity of platforms and environments. In this paper, we present ThermWare, a non-intrusive screening method to detect anomalous operations on embedded devices at run-time. ThermWare relies on the observation that electronic circuits generate subtle patterns of heat at the component level when the corresponding module is accessed by the micro-operations (e.g., file-write) of the running code. We propose the use of these side-channel heat signatures captured by a thermal camera to determine the sequence of underlying computations in real time. An early implementation of ThermWare shows success in detecting common malware routines in general-purpose IoT devices. We envision leveraging the thermal side-channel to track the internal operations of an embedded device, which can potentially lead to broader applications in engineering embedded systems, monitoring device health and run-time capacity, assisting embedded coding optimization, and physical layer security analysis.Item Sirius: A Self-Localization System for Resource-Constrained IoT Sensors(Association for Computer Machinery (ACM), 2023-06-18) Garg, Nakul; Roy, NirupamLow-power sensor networks are transforming large-scale sensing in precision farming, livestock tracking, climate-monitoring and surveying. Accurate and robust localization in such low-power sensor nodes has never been as crucial as it is today. This paper presents, Sirius, a self-localization system using a single receiver for low-power IoT nodes. Traditionally, systems have relied on antenna arrays and tight synchronization to estimate angle-of-arrival (AoA) and time-of-flight with known access points. While these techniques work well for regular mobile systems, low-power IoT nodes lack the resources to support these complex systems. Sirius explores the use of gain-pattern reconfigurable antennas with passive envelope detector-based radios to perform AoA estimation without requiring any kind of synchronization. It shows a technique to embed direction specific codes to the received signals which are transparent to regular communication channel but carry AoA information with them. Sirius embeds these direction-specific codes by using reconfigurable antennas and fluctuating the gain pattern of the antenna. Our prototype demonstrates a median error of 7 degrees in AoA estimation and 2.5 meters in localization, which is similar to state-of-the-art antenna array-based systems. Sirius opens up new possibilities for low-power IoT nodes.