Local AI Risk Engine
In traditional payment systems, fraud detection is handled by centralized servers, machine learning platforms, and payment processors that monitor behavior, analyze trends, and block suspicious transactions in real time.
DashPay takes a radically different approach.
To maintain user privacy and offline compatibility, DashPay introduces the Local AI Risk Engine — a lightweight, on-device system designed to perform real-time risk evaluation, behavioral checks, and proof-level integrity analysis without external dependencies.
This engine allows each device to act as its own risk validator, eliminating the need for centralized trust while retaining strong security guarantees.
Why Risk Matters in Offline Payments
In offline environments, you can't rely on:
Live chain state
Real-time double-spend detection
Cloud-based identity or behavior scoring
Third-party fraud APIs
DashPay solves this by equipping each wallet or terminal with a context-aware, self-contained risk model that actively monitors and filters invalid or malicious behavior before it enters the system.
How It Works
Local Proof Validation Every payment proof received is scanned for internal consistency:
ZK proof validity
Expiry window (TTL)
Signature match
Nonce structure
Rate of use from given device
Behavioral Pattern Monitoring The engine continuously tracks device-level behavior to detect unusual patterns:
Rapid repeated attempts
Out-of-sequence payments
Suspicious retry loops
Latent proof injection attempts
Anomaly Flagging & Soft Lock If suspicious activity is detected, the engine can:
Mark the payment as suspicious
Reject it outright
Soft-lock the device until reconnection or reset
Queue flagged data for audit at sync time
No Cloud Required All evaluations are done locally — there is no telemetry, no tracking, and no external callouts. Devices protect themselves, and sync-time logic ensures consensus finality.
Security Features
Anti-Replay Protections — Prevents old or duplicated proofs from being reused
Device Rate Limits — Prevents rapid abuse, flash spam, or balance draining
Nonce Tracking — Each transaction carries a cryptographic nonce checked against local history
Time-Bound Proofs — Every proof must be used within a valid time window
Autonomous Decision-Making — No dependence on cloud or third-party approval
Why It’s Different
Unlike centralized fraud tools, DashPay’s Risk Engine is:
Privacy-preserving — No behavioral data ever leaves the device
Instant — Doesn’t wait on backend verification or chain finality
Always-on — Operates in fully offline environments
Composable — Can be updated, extended, or replaced by custom policies
When It’s Used
A user taps their phone to a vending machine — proof is checked on the spot
A peer sends a payment in a low-signal zone — their behavior is evaluated locally
A merchant device encounters a flurry of retries — the engine throttles and flags
A bot tries to abuse rate limits — the device self-locks or defers until reconnect
The Local AI Risk Engine is how DashPay ensures zero-trust integrity in zero-connectivity environments — securing the system from the edge, without sacrificing privacy or UX.
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