Compare Revelock vs. TrustDecision

We create a unique digital fingerprint for every user by analyzing a combination of biometric data, behavioral patterns, device specifics, IP information, and network insights, ensuring ongoing verification throughout the user journey. In addition to identifying threats, our platform allows you to implement customizable policies that automatically counter malware, phishing attempts, and remote access Trojans through Revelock Active Defense. The BionicID™ is constructed from an extensive array of parameters derived from behavioral biometrics, analytics, device information, network data, and threat intelligence. This innovative BionicID™ can authenticate users after just two interactions, significantly cutting down on both false positives and false negatives that can hinder user experience and overwhelm your support team. Regardless of the attack vector—be it malware, RATs, phishing, identity theft, impersonation, or manipulation—the BionicID™ fundamentally transforms security measures. Our advanced anomaly detection and classification engine provides ongoing risk evaluation, safeguarding your users while effectively preventing fraud. With this robust system, organizations can enhance their security posture and improve user trust.

Accurately differentiating between authentic users and potential threats requires the real-time identification of unique devices and the analysis of global historical data. However, device characteristics may evolve over time, which can lead to misidentifying the same device as a different entity. It is essential to gather ample data while ensuring user privacy is upheld, particularly in light of rigorous data protection laws. As new devices and operating systems are frequently introduced, remaining current and flexible is crucial for effective identification. Additionally, linking multiple device profiles to a single user necessitates a robust capability for cross-device tracking to maintain accuracy. There is also the challenge of manipulating user-agent information sent by browsers or applications to replicate legitimate device behavior. Maintaining a distinct device ID can be complicated when it faces tampering, modifications, or hijacking attempts. Moreover, distinguishing each device becomes increasingly difficult in challenging scenarios, such as factory resets, altered device locations, the detection of group control tools, script-based manipulations, and app reinstalls. Continuous innovation in detection techniques will be essential to address these evolving challenges effectively.