Welcome
John Wu
9:00am - 9:10am EDT

Keynote Speech
Chair: John Wu
9:10am - 10:00am EDT

Keynote Presentation
    Dr. David Mohaisen, University of Central Florida
    Title: Understanding the Privacy Dimension of Wearables through Machine Learning-enabled Inferences

    Abstract: To keep up with the ever-growing user expectations, developers keep adding new features to augment the use cases of wearables, such as fitness trackers, augmented reality head-mounted devices (AR HMDs), and smart watches, without considering their security and privacy impacts. In this talk, I will introduce our recent results on understanding the privacy dimension of wearables through inference attacks facilitated by machine learning and open research directions. First, I will present an exploration of the attack surface introduced by fitness trackers. We propose an inference attack that breaches location privacy through the elevation profiles collected by fitness trackers. Our attack highlights that adversaries can infer the location from elevation profiles collected via fitness trackers. Second, I will review the attack surface introduced by smartwatches by developing an inference attack that exploits the smartwatch microphone to capture the acoustic emanations of physical keyboards and successfully infers what the user has been typing. Third, I will present an exploration of the AR HMD’s through the design of an inference attack that exploits the geometric projection of hand movements in the air. The attack framework predicts the typed text on an in-air tapping keyboard, which is only visible to the user. I will conclude with lessons learned, defense directions, and open research directions.

Bio: David Mohaisen (PhD’12, University of Minnesota) is a Full Professor of Computer Science at the University of Central Florida, where he has been since 2017. Previously, he was an Assistant Professor at SUNY Buffalo (2015-2017) and a Senior Scientist at Verisign Labs (2012-2015). His research interests are in applied security and privacy, covering aspects of networked systems, software systems, IoT and AR/VR, machine learning, and blockchain systems. His research has been supported by several generous grants from NSF, NRF, AFRL, AFOSR, etc., and has been published in top conferences and journals, with multiple best paper awards. His work was featured in multiple outlets, including the New Scientist, MIT Technology Review, ACM Tech News, Science Daily, etc. Among other services, he is currently an Associate Editor of IEEE Transactions on Dependable and Secure Computing and served as an Associate Editor of IEEE Transactions on Mobile Computing (2 terms), IEEE Transactions on Parallel and Distributed Systems (1 term), and IEEE Transactions on Cloud Computing (1 term). He is a senior member of ACM (2018) and IEEE (2015), a Distinguished Speaker of the ACM, and a Distinguished Visitor of the IEEE Computer Society. Visit https://www.cs.ucf.edu/~mohaisen/ for more information.     

Break

10:00am - 10:15am EDT

Technical Sessions

Chair: John Wu
10:15am - 12:00pm EDT

Towards Securing UAV Flying Base Station: Misplacement Impact Analyses on Battery and Power
    Sang-Yoon Chang, Kyungmin Park, Jonghyun Kim and Jinoh Kim

Insights into DoH: Traffic classification for DNS over HTTPS in an Encrypted Network
    Fatema Bannat Wala, Scott Campbell and Mariam Kiran

Analyzing Transatlantic Network Traffic over Scientific Data Caches
    Ziyue Deng, Alex Sim, Kesheng Wu, Chin Guok, Damian Hazen, Inder Monga, Fabio Andrijauskas, Frank Wurthwein and Derek Weitzel

Evaluating Unbalanced Network Data for Attack Detection
    Donghwoon Kwon, Rares-Mihail Neagu, Prem Rasakonda, Jeong-Tak Ryu and Jinoh Kim