Abstract: Today, with the rapid expansion of the Internet of Things (IoT), we face a new world, where we are never alone. At all times, a plethora of connected devices, from smartphones to home assistants to IoT, sense and monitor our activities. Moreover, these devices are often backed by powerful analytics to sift through large volume of personal data, at times collected without our awareness or consent.

In this talk, I will describe how sensors such as accelerometers and gyroscopes embedded in smart devices can be exploited to track users online, under real-world settings, to infer personal interests and habits. I will also discuss how such sensors are being used in the wild, and how effective existing privacy protection mechanisms are at restricting access to sensor data. Finally, I will discuss usable countermeasures I have developed to protect users against such invasive tracking techniques, as well as our ongoing work to address privacy concerns for a growing number of other emerging IoT scenarios.

Short Bio: Anupam Das is a Postdoctoral Fellow in the School of Computer Science at Carnegie Mellon University. His research interests lie in the domain of security and privacy with a focus on understanding and mitigating the security and privacy risks of emerging technologies. He received his Ph.D. in Computer Science in 2016 from the University of Illinois at Urbana-Champaign where he was a recipient of Fulbright Science and Technology fellowship. He previously served as an Assistant Professor in the department of Computer Science and Engineering at the Bangladesh University of Engineering and Technology. He is recipient of two ACM Distinguished Paper Awards (ASIACCS 14, MMSys 17)