Visible to the public Cloud-Assisted IoT Systems Privacy--2020Q3Conflict Detection Enabled

Submitted by FengjunLi on Sun, 10/11/2020 - 10:58pm

PI(s), Co-PI(s), Researchers: Fengjun Li, Bo Luo

HARD PROBLEM(S) ADDRESSED

The goal of this project is to develop principles and techniques to model privacy needs, threats, and protection mechanisms in cloud-assisted IoT systems. The work aims to address the hard problems of resilient architectures, security metrics as well as scalability and composability.

PUBLIC ACCOMPLISHMENT HIGHLIGHTS

  • In this quarter, we are working on two projects: (1) IoTPrivacyChecker: develop a privacy risk analysis system to automatically extract information about privacy-related data collection and usage from the IoT app's description, user interface and code, and compile a privacy usage description to help users understand the privacy policy and privacy risk of an IoT app. (2) IoT Para-rehosting: design a new para-rehosting technique to realize re-hosting of microcontroller operating systems and software on commodity hardware. This technique will address the performance, scalability and visibility issues in finding bugs in microcontroller firmware.

PUBLICATIONS

  • Lingjing Yu, Bo Luo, Jun Ma, Zhaoyu Zhou, and Qingyun Liu. You Are What You Broadcast: Identification of Mobile and IoT Devices from (Public) WiFi. In USENIX Security Symposium, August 12-14, 2020.

  • Abdulmalik Humayed, Fengjun Li, Jingqiang Lin, and Bo Luo. CANSentry: Securing CAN-Based Cyber-Physical Systems against Denial and Spoofing Attacks. In European Symposium on Research in Computer Security (ESORICS), September 14-18, 2020.

  • Sohaib Kiani, Sana Awan, Fengjun Li, Bo Luo and Jun Huan, "WOLF: Automated Machine Learning Workflow Management Framework for Malware Detection and Other Applications," in Symposium on the Science of Security (HotSoS), September 22-14, 2020.

  • Sohaib Kiani, Fengjun Li, Chao Lan and Bo Luo, "DETGEN: Adversarial Detection using Partially Generated Images," in HotSoS WIP session, September 22-14, 2020.

  • Sana Awan, Fengjun Li and Bo Luo, "A Federated Transfer Learning Framework for IoT Applications," in HotSoS WIP session, September 22-14, 2020.

  • Hao Xue, Qiaozhi Wang, Bo Luo, Chao Lan and Fengjun Li, "Detecting Bots via Surrounding Neighborhoods," in HotSoS WIP session, September 22-14, 2020.

COMMUNITY ENGAGEMENTS

  • Fengjun Li served on the "Cybersecurity Research and Education" panel in the 2nd International Workshop on Cyber Security and Data Privacy, July 18, 2020.

EDUCATIONAL ADVANCES

N/A

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