On building interactive and secure smart spaces

Dr Swadhin Pradhan, UT Austin

Short Bio:
Swadhin Pradhan is a recent PhD graduate in the Department of Computer Science at UT Austin. His research is focused on mobile computing and internet-of-things (IoT) systems. He has designed, built, and deployed systems that deliver ubiquitous sensing, enhanced communication capabilities, and new human-computer interfaces. His works have been published in the top-tier conferences like MobiCom, CHI, UbiComp, Infocom, etc. and featured in the popular press like BBC, MIT Tech Review, Boston Globe, The Guardian, etc. He is a recipient of the UT Austin Graduate Fellowship and the University Gold Medal at Jadavpur University, Kolkata.

Date:Aug 20,
Time: 7:30 PM IST

Meet Link:


The future of Internet-of-Things (IoT) demands seamless interaction between users and devices, where sensing interfaces blend into everyday objects. Toward realizing the vision of making sensing interfaces truly ubiquitous, we also need to make the future smart spaces secure. In this talk, I will present two of my works, which concern with these critical issues. Firstly, I will present RIO, a novel battery-free touch-sensing user interface (UI) primitive. With RIO, any surface can be turned into a touch-aware interactive surface by directly attaching RFID tags. RIO is built using impedance tracking: when a human finger touches the surface of an RFID tag, the impedance of the antenna changes. This change manifests as a variation in the phase of the RFID backscattered signal and is used by RIO to track fine-grained touch movement, over both off-the-shelf and custom-built tags. Secondly, I will present REVOLT, an end-to-end system to detect replay attacks on voice-first devices (e.g., Amazon Echo, Google Home, etc.) without requiring a user to wear any wearable device. This system has several distinct features: (i) it intelligently exploits the inherent differences between the spectral characteristics of the original and replayed voice signals, (ii) it exploits both acoustic and WiFi channels in tandem, (iii) it utilizes unique breathing rate extracted from WiFi signal while speaking to test the liveness of human voice. This novel technique of combining WiFi and voice modality yields low false positive and false negative when evaluated against a range of voice replay attacks.