Projects

Our research interests span across network, mobile, software, hardware, and human, emphasizing security and privacy issues of the targets. Details will be posted when they become publicly available.

  • Voice Assistant Security
    • Audio Hotspot Attack
  • AI Security
  • Autonomous Vehicle Security
  • New Authentication mechanisms
    • Biosignal-based authentication
    • VR authentication
    • Usable authentication for visually impaired person
  • Offensive Security
    • RouteDetector — A novel PoC side-channel attack for mobile devices
    • Tap ‘N Ghost
    • Analysis of RF retroreflector
    • Social Accounts De-anonymization
    • De-anonymizing online purchase history
  • Mobile Security
    • ACODE — Analysing mobile apps with static software analysis and natural language processing
    • AppRaiser — A system that automatically detects “cloned” Android apps
    • PADetector — A system that can detect promotional attackers on the Android app marketplaces.
    • Analytics of mobile app market
  • IoT
  • Human-factors in security / Usable Security
    • Accessible Security — Authentication mechanisms for visually impaired person [paper][poster]
    • Passwords analytics
    • Usable and secure pattern rock system
    • User security perception on the Android marketplace
  • Privacy
    • Understanding web tracking in the wild
    • Android app privacy
    • Auction privacy
    • Privacy Policy analysis
    • Privacy of the GAEN framework
  • Network Security
    • ShamFinder  — A framework that detects homograph IDN.
    • AutoBLG — Automated blacklist generation framework.
    • SFMap — Inferring hostnames of encrypted HTTP traffic
    • Detecting malicious traffic
    • Darknet analysis — Extracting useful information from darknet traffic
    • CLAP — Classification of potentially unwanted applicatons (PUA)
    • COVID-19 domain names
    • Olympic domain names
    • DNS Security mechanisms
  • Software Security
    • Malware analytics — Applying machine learning techniques to analyzing malware samples
    • Scalable vulnerability detection