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Banking & Finance
Branch-floor robots that distinguish a regular customer from a social-engineering visitor wearing the same clothes. Vault-room access with continuous liveness, not gated checkpoints.
Behavioral Biometrics for Robotics
Identify people by who they are, not what they look like.
A hardware module for robots that recognizes humans through gait, posture, height, voice, and dozens of other behavioral signals. Mask-proof. Deepfake-proof. On-device.
On-device inference
GDPR / CCPA aligned
Sub-200ms latency
97%
re-identification accuracy
internal benchmark, controlled environments
internal benchmark, controlled environments
40+
behavioral signals fused
per identity profile
per identity profile
<200ms
edge inference
no cloud round-trip
no cloud round-trip
0
biometric data sent off-device
by default configuration
by default configuration
The Problem
Faces can be faked. Behavior cannot.
Facial recognition is a single-signal system, and a single signal is a single point of failure. Silicone masks, deepfake reconstructions, identical twins, and adversarial accessories all defeat it. For robots operating in banks, data centers, and critical infrastructure, that is not an acceptable risk.
Facial recognition
Single signal, single failure mode
Face match98.4%
LivenessPASS
VerdictAUTHORIZED ✗
False positive — mask defeats the only signal in use.
Securero behavioral
Multi-signal, fused, mask-blind
Gait fingerprintMISMATCH
Height + ratiosMISMATCH
Voice signatureMISMATCH
VerdictDENIED ✓
Mask is irrelevant — the body underneath does not match.
A real attacker doesn't get to choose which signals to spoof. They have to spoof all of them — at the same time, in motion, in real time. The combinatorial cost is what makes behavioral biometrics structurally harder to defeat.
Our Solution
A drop-in module for any compatible robot.
Securero is a hardware co-processor that mounts onto a robot's existing sensor head and fuses its inputs into a single behavioral identity engine.
The module pulls signals from the robot's RGB camera, depth/LiDAR sensor, IMU, and microphone array. Onboard, a dedicated neural accelerator builds a continuously-updated behavioral profile of every person the robot observes — without sending raw biometric data anywhere.
Integration is a wiring loom and a software SDK. Most platforms are deployable in under a day. Profiles are stored encrypted on-device, retained only for the period the customer configures, and never leave the robot unless the customer explicitly opts in to a federated training pool.
- No cloud dependency. The robot identifies people whether or not it has network connectivity.
- Adversarial-aware. Mask, lighting, partial occlusion, and adversarial-clothing attacks are detected as anomalies, not silently misclassified.
- Continuous, not gated. Identity is re-verified every frame — there is no “authenticated session” to hijack.
SR-MOD/01
REV-D
SR-MOD/01 reference unit. Production OEM variants available on request.
Technology
What a behavioral fingerprint actually contains.
Each signal below is weak on its own. Fused, they form an identity profile that is statistically prohibitive to spoof.
Height
Stereo depth from the robot's sensor head triangulates standing height to ±1.5 cm at 5 m. Sufficient on its own to eliminate roughly 90% of population candidates.
Hover or tap any marker. The full production profile combines 40+ such signals; only a representative subset is shown here.
Pipeline
How it works, end to end.
01
Capture
The module subscribes to the robot's existing camera, depth, IMU, and microphone streams. No additional sensors are required for most platforms.
02
Profile
An on-device neural pipeline extracts and fuses 40+ behavioral features into an encrypted identity vector. Profiles update continuously as the subject moves.
03
Verify
Live profiles are matched against the customer's authorized roster every frame. The robot's host system receives a confidence score plus an anomaly flag for spoofing attempts.
Where It Matters
Built for environments where mistakes are expensive.
Critical Infrastructure
Patrol robots in data centers, substations, and water-treatment facilities. Tailgating is detected behaviorally — two distinct gait profiles passing one badge swipe is flagged immediately.
Defense & Force Protection
Perimeter-patrol UGVs that re-identify friendlies after sensor handoff. Operates without GPS, without network, in dust, smoke, and low-light conditions.
Retail & Loss Prevention
Store-floor robots that recognize organized retail crime crews on their second visit, by the way they move — even when they change clothes, hairstyles, and accessories.
Hardware
SR-MOD/01 reference specifications.
| Form factor | 72 × 48 × 11 mm SoM, M.2-2280 carrier optional |
|---|---|
| Compute | Dedicated NPU, 8 TOPS INT8 sustained · ARM Cortex-A78 quad-core host · ISP + DSP co-processors |
| Sensor inputs | 4× MIPI-CSI camera lanes · I2S audio (4-mic array) · CAN-FD · USB 3.2 · 1× 1G Ethernet |
| Power | 5 W typical, 9 W peak · 5 V / 12 V input |
| Inference latency | < 200 ms end-to-end (sensor → verdict) at 30 Hz frame rate |
| On-device storage | 32 GB eMMC encrypted (XTS-AES 256), expandable via secure slot |
| Operating environment | −20 °C to +60 °C · IP54 with carrier · MIL-STD-810H shock and vibration profile (in qualification) |
| Supported robot platforms | ROS 2 (Humble, Jazzy) · NVIDIA Isaac · custom integrations via gRPC SDK |
| Compliance roadmap | SOC 2 Type II (in audit) · ISO/IEC 27001 (in audit) · GDPR & CCPA aligned by design |
Procurement. Production OEM variants — different power envelopes, ruggedization tiers, sensor fan-outs — are available under NDA. Contact us for a sample unit and integration call.
Privacy by Design
Biometrics done responsibly is the only way it stays viable.
Behavioral biometrics is more powerful than facial recognition — which is exactly why we engineered it under stricter constraints, not looser ones.
- On-device processing. Identity profiles are computed and matched on the robot. Raw audio, video, and depth never leave the device by default.
- Customer-controlled retention. Profile lifetime is a customer setting, with a hard cap. Default is 30 days.
- Explicit consent paths. Federated learning, profile sharing across fleet units, and any cloud upload are off by default and gated by signed customer policy.
- No covert deployment. SDK requires the integrator to surface a notice mechanism in the host application.
- Auditable decisions. Every verification event produces a signed, hashable record for compliance and post-incident review.
Full details in our Privacy Policy.
About
A focused team building hardware for a focused problem.
Securero is an Israeli robotics-security company. Our founding team comes from defense biometrics, semiconductor design, and robotics platform engineering. We sell to systems integrators and robot OEMs who require behavioral identity as a built-in capability of their platform — not a bolted-on cloud service.
Working with
Contact
Talk to engineering.
Every deployment starts with a thirty-minute call. Tell us about the platform, the environment, and the threat model — we'll tell you whether we're the right fit.
Or reach us directly at: info@securero.io