GeeTest Device Fingerprinting is a Fraud & Account Takeover Prevention product by GeeTest. Pricing is commercial (price not published).
GeeTest Device Fingerprinting is a device identification and risk analysis product used to distinguish genuine users from fraudulent traffic across web and mobile applications. The product collects device and app-level attributes to generate a unique device identifier without relying primarily on identifiers such as IMEI or IDFA. It aims to maintain consistent fingerprints for a device across multiple apps and after app reinstallation. The system applies what the vendor calls Triple-Dimensional Review Technology, analyzing historical, attribution, and risk data to evaluate traffic on desktop and mobile. It generates risk labels (up to 40) covering device and behavior perspectives to flag suspicious requests, and visualizes relationships between devices and accounts using a graph convolutional network (GCN)-based device relationship graph. This is used to detect duplicate or linked accounts and map traffic requests to devices and accounts. Reported accuracy claims include over 99.5% fingerprint accuracy and a stated less-than-0.0001% chance of generating identical fingerprints for different devices. Use cases described include marketing (ad fraud prevention, ad targeting, data analysis), finance (fraud and identity theft prevention, transaction security), e-commerce (marketing, personalized recommendations, fraud prevention, account security), and gaming (anti-cheat, malicious behavior detection).</description> <parameter name="summary">Device fingerprinting and risk analysis product for fraud detection across web and mobile
Common questions about GeeTest Device Fingerprinting including features, pricing, alternatives, and user reviews.
GeeTest Device Fingerprinting is GeeTest Device Fingerprinting is a device identification and risk analysis product used to distinguish genuine users from fraudulent traffic across web and mobile applications.
The product collects device and app-level attributes to generate a unique device identifier without relying primarily on identifiers such as IMEI or IDFA. It aims to maintain consistent fingerprints for a device across multiple apps and after app reinstallation.
The system applies what the vendor calls Triple-Dimensional Review Technology, analyzing historical, attribution, and risk data to evaluate traffic on desktop and mobile. It generates risk labels (up to 40) covering device and behavior perspectives to flag suspicious requests, and visualizes relationships between devices and accounts using a graph convolutional network (GCN)-based device relationship graph. This is used to detect duplicate or linked accounts and map traffic requests to devices and accounts.
Reported accuracy claims include over 99.5% fingerprint accuracy and a stated less-than-0.0001% chance of generating identical fingerprints for different devices.
Use cases described include marketing (ad fraud prevention, ad targeting, data analysis), finance (fraud and identity theft prevention, transaction security), e-commerce (marketing, personalized recommendations, fraud prevention, account security), and gaming (anti-cheat, malicious behavior detection).
GeeTest Device Fingerprinting is built for security teams handling Fraud Detection, Anomaly Detection, Graph, Android Security. Teams typically adopt GeeTest Device Fingerprinting when they need to fraud & payment security capabilities integrated into their existing stack. Explore similar tools at https://cybersectools.com/alternatives/geetest-device-fingerprinting
GeeTest Device Fingerprinting is a commercial Fraud & Payment Security solution. For detailed pricing information, visit https://www.geetest.com/en/device-fingerprinting or contact GeeTest directly.
Popular alternatives to GeeTest Device Fingerprinting include:
Compare all GeeTest Device Fingerprinting alternatives at https://cybersectools.com/alternatives/geetest-device-fingerprinting
GeeTest Device Fingerprinting is for security teams and organizations that need Fraud Detection, Anomaly Detection, Graph, Android Security, IOS. It's particularly suitable for enterprises requiring robust, commercial-grade security capabilities. Other Fraud & Payment Security tools can be found at https://cybersectools.com/categories/fraud-payment-security
Head-to-head feature, pricing, and rating breakdowns.
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