AShield solution is built on both deterministic and probabilistic techniques and the threats are blocked at three fences, one of which is AI/ML based. User behavior patterns are profiled and suspicious behavior is flagged. Any anomaly caused within the IP or telecom network is detected and based on severity, appropriate fraud score is applied and policies are enforced.
Detect threats and reduce the time of attack, in turn reducing damage. Detection happens in multiple fences thus covering most threats
Reduce volume of attack by blocking threats before they affect the organization. Multi-fenced approach ensures various threats are caught at different stages
Identify key user and session parameters and enforce policies on detection of threats. Crypto challenges are thrown only when a potential threat is detected.
ML model continuously learns from good and bad user patterns. The prediction is used to enforce a challenge. This fence catches anomalies that may not have been caught by deterministic techniques
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