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.

• AI Security
  • Attack against machine learning algorithms
  • Attack against cyber-physical systems empowered by AI
• Autonomous Vehicle Security
  • Attack against LiDAR sensors
  • Attack against AI-cameras
  • Attack against end-to-end autonomous driving systems
• New Authentication mechanisms
  • BioSignal-based authentication (BlinkAuth)
  • VR authentication (PinchKey)
  • World-based authentication with LiDAR sensors (WorldAuth)
  • Rythm-based authenticatoin
  • 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

• Voice Assistant Security & Privacy
  • Audio Hotspot Attack
  • ChatterBox framework
•  IoT
  • Trojan of Things
  • RF retroreflectors
  • AI Speakers
  • EEG diagnosis systems
  • Robot Security
  • Analog Signal Firewall
• 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
  • Privacy policy analysis with transformers
• 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
• 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
  • Online banking flauding analysis
  • Browser permission mechanisms
• Software Security
  • Malware analytics — Applying machine learning techniques to analyzing malware samples
  • Scalable vulnerability detection
  • VR app analysis