Yanzi Zhu (UC Santa Barbara), Zhujun Xiao (University of Chicago), Yuxin Chen (University of Chicago), Zhijing Li (UC Santa Barbara), Max Liu (University of Chicago), Ben Y. Zhao (University of Chicago), Heather Zheng (University of Chicago)

Wireless devices are everywhere, constantly bombarding us with transmissions across a wide range of RF frequencies. Many of these invisible transmissions reflect off our bodies, carrying off information about our location, movement, and other physiological properties. While a boon to professionals with carefully calibrated instruments, they may also be revealing our physical
status to potential attackers nearby.

Our work demonstrates a new set of silent reconnaissance attacks that leverages the presence of commodity WiFi devices to track users inside private homes and offices, without compromising any WiFi network, data packets, or devices. We show that just by sniffing existing WiFi signals, an
adversary can accurately detect and track movements of users inside a building. This is made possible by our new signal model that links together human motion near WiFi transmitters and variance of multipath signal propagation seen by the attacker sniffer outside of the property.
These attacks are cheap, highly effective, and difficult to detect. We implement
the attack using a single commodity smartphone, and deploy it in 11 real-world offices and residential apartments, and show it is highly effective. Finally, we evaluate potential defenses, and
propose a practical and effective defense based on AP signal obfuscation.

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DefRec: Establishing Physical Function Virtualization to Disrupt Reconnaissance of...

Hui Lin (University of Nevada, Reno), Jianing Zhuang (University of Nevada, Reno), Yih-Chun Hu (University of Illinois, Urbana-Champaign), Huayu Zhou (University of Nevada, Reno)

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CloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples

Honggang Yu (University of Florida), Kaichen Yang (University of Florida), Teng Zhang (University of Central Florida), Yun-Yun Tsai (National Tsing Hua University), Tsung-Yi Ho (National Tsing Hua University), Yier Jin (University of Florida)

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Secure Sublinear Time Differentially Private Median Computation

Jonas Böhler (SAP Security Research), Florian Kerschbaum (University of Waterloo)

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HotFuzz: Discovering Algorithmic Denial-of-Service Vulnerabilities Through Guided Micro-Fuzzing

William Blair (Boston University), Andrea Mambretti (Northeastern University), Sajjad Arshad (Northeastern University), Michael Weissbacher (Northeastern University), William Robertson (Northeastern University), Engin Kirda (Northeastern University), Manuel Egele (Boston University)

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