DARVS - Deepfake Authentication & Reality Verification System
Back to PortfolioVerifies identity under physical presence constraints.
Authentication requires ALL conditions to pass. No partial success.
Live System Panel
STATUS: SCANNING
Confidence
90.0%
Processing Time
246 ms
STATE: SCANNING
Low FPS due to per-frame MTCNN inference (security prioritized over speed)
Execution Environment
- • Laptop-based real-time processing (OpenCV + TensorFlow)
- • Multi-stage pipeline tuned for accuracy versus performance
- • Designed under real-time response and system latency constraints
Pipeline
System ExecutionAnimation is matched with System's live Status
Camera
MTCNN
Anti-Spoof
Liveness
FaceNet
Decision
Interactive Breakdown (Click on a step to understand it better.)
Purpose
Acquire live frame sequence
Why Chosen
Enables temporal verification
Prevents
Static image bypass
System Validation
[✓] Real UserAUTHORIZED
[✗] Photo SpoofBLOCKED
[✗] Screen ReplayBLOCKED
[✗] No LivenessREJECTED
Security Logging
Threat Rejection Rate: 33%Total Attempts: 42Successful Auth: 28Rejected Attacks: 14Sample every 1.5s
Engineering Decisions
MTCNN - robust face detection under pose and lighting variation.
FaceNet - embedding thresholding enables deterministic identity acceptance.
Pipeline - sequential multi-stage gating blocks partial-pass authentication.
Security Philosophy
DARVS uses AI + sensing-based verification where identity is accepted only after liveness, anti-spoof, and embedding agreement pass in gated sequence.
System Summary
DARVS enforces identity verification through multi-stage gated execution combining liveness, anti-spoofing, and embedding-based matching.