Daoyuan Wu (Singapore Management University), Debin Gao (Singapore Management University), Rocky K. C. Chang (The Hong Kong Polytechnic University), En He (China Electronic Technology Cyber Security Co., Ltd.), Eric K. T. Cheng (The Hong Kong Polytechnic University), Robert H. Deng (Singapore Management University)

Open TCP/UDP ports are traditionally used by servers to provide application services, but they are also found in many Android apps. In this paper, we present the first open-port analysis pipeline, covering the discovery, diagnosis, and security assessment, to systematically understand open ports in Android apps and their threats. We design and deploy a novel on-device crowdsourcing app and its server-side analytic engine to continuously monitor open ports in the wild. Over a period of ten months, we have collected over 40 million port monitoring records from 3,293 users in 136 countries worldwide, which allow us to observe the actual execution of open ports in 925 popular apps and 725 built-in system apps. The crowdsourcing also provides us a more accurate view of the pervasiveness of open ports in Android apps at 15.3%, much higher than the previous estimation of 6.8%. We also develop a new static diagnostic tool to reveal that 61.8% of the open-port apps are solely due to embedded SDKs, and 20.7% suffer from insecure API usages. Finally, we perform three security assessments of open ports: (i) vulnerability analysis revealing five vulnerability patterns in open ports of popular apps, e.g., Instagram, Samsung Gear, Skype, and the widely-embedded Facebook SDK, (ii) inter-device connectivity measurement in 224 cellular networks and 2,181 WiFi networks through crowdsourced network scans, and (iii) experimental demonstration of effective denial-of-service attacks against mobile open ports.

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Please Forget Where I Was Last Summer: The Privacy...

Kostas Drakonakis (FORTH, Greece), Panagiotis Ilia (FORTH, Greece), Sotiris Ioannidis (FORTH, Greece), Jason Polakis (University of Illinois at Chicago, USA)

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Stealthy Adversarial Perturbations Against Real-Time Video Classification Systems

Shasha Li (University of California Riverside), Ajaya Neupane (University of California Riverside), Sujoy Paul (University of California Riverside), Chengyu Song (University of California Riverside), Srikanth V. Krishnamurthy (University of California Riverside), Amit K. Roy Chowdhury (University of California Riverside), Ananthram Swami (United States Army Research Laboratory)

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TextBugger: Generating Adversarial Text Against Real-world Applications

Jinfeng Li (Zhejiang University), Shouling Ji (Zhejiang University), Tianyu Du (Zhejiang University), Bo Li (University of California, Berkeley), Ting Wang (Lehigh University)

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Measurement and Analysis of Hajime, a Peer-to-peer IoT Botnet

Stephen Herwig (University of Maryland), Katura Harvey (University of Maryland, Max Planck Institute for Software Systems (MPI-SWS)), George Hughey (University of Maryland), Richard Roberts (University of Maryland, Max Planck Institute for Software Systems (MPI-SWS)), Dave Levin (University of Maryland)

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Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)