AdShield

Detect and prevent fraud in real-time using advanced fingerprint identification. Track suspicious activities across devices and accounts effortlessly no fraudster can hide!

Comment

AdShield – Smart Fraud Detection. Zero Guesswork.

Inspiration

Online fraud is a growing threat, from fake e-commerce transactions to social media scams. Inspired by the need for better fraud prevention, we set out to build a system that detects suspicious behavior in real time using Fingerprint’s device intelligence and Smart Signals.

What It Does

AdShield continuously monitors user interactions on a platform (e-commerce, social media, etc.) and flags fraudulent activities such as:

  • Multiple accounts from the same device (fake reviews, scam accounts).
  • One payment method used by many visitor IDs (stolen credit cards).
  • Rapid, unusual clicking patterns (bot-like behavior).
  • Users frequently switching identities (account takeovers).
    Once detected, these activities are flagged in an admin dashboard with real-time alerts.

How We Built It

  • Frontend: React + Tailwind CSS for the fraud detection dashboard.
  • Tracking: A JavaScript script embedded in target websites to collect visitor interactions.
  • Fraud Detection: Fingerprint API to identify unique users across multiple sessions and detect anomalies.

Challenges We Ran Into

  • Fine-tuning fraud detection rules to balance security and avoid false positives.
  • Real-time data processing to detect and flag fraud instantly.
  • Integrating Fingerprint API effectively without impacting website performance.

Accomplishments That We're Proud Of

  • Successfully built an automated fraud detection system that works across different platforms.
  • Developed a real-time fraud monitoring dashboard for admins.
  • Implemented seamless tracking without requiring users to sign up or install anything.

What We Learned

  • How fraudsters exploit online platforms and techniques to detect them.
  • Leveraging device fingerprinting for security and fraud prevention.
  • Building scalable fraud detection systems with real-time alerting.

What's Next for AdShield

  • Expanding fraud detection models using machine learning for more accuracy.
  • Enhancing alert mechanisms with email/SMS notifications for high-risk activities.
  • Supporting more integrations for platforms beyond e-commerce and social media.
Share this project:

Updates