Use Cases in Cybersecurity & Digital Wallets

Quantum-Inspired Cybersecurity & Digital Wallet Protection

Anomaly Detection in User Behavior:

Quantum-inspired models analyze login patterns, access logs, and device behavior to detect subtle deviations that may indicate fraud, account takeover, or bot activity.

Digital Wallet Anomaly Detection:

Detect inconsistent spending patterns, device switches, or time/location anomalies in e-wallet activity — even when individual transactions appear normal.

Transaction Graph Analysis for Fraud Rings:

Using graph-based QUBO models, related transactions across wallets or accounts are linked — helping uncover coordinated fraud attempts or money laundering paths.

Behavior Fingerprinting for Digital Wallets:

IEach wallet has a “behavioral fingerprint” based on time, frequency, amounts, counterparties. HessQ flags deviations.

Multi-Factor Risk Optimization for Wallet Transactions:

Optimize thresholds and rules across many dimensions: transaction size, KYC status, blacklist scoring, velocity.

Identity Impersonation Detection in User Sessions:

Track session activity and detect if an account is being used by someone who isn’t the rightful owner.