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FORENSIC TRANSPARENCY & PEER DEFENSE

Detection Methodology, Benchmarks & Limitations

In forensic media authentication, ungrounded accuracy claims are counter-productive. This document specifies the exact benchmark datasets, sample sizes, class balances, false-positive/negative rates, latency profiles, and known boundaries governing the Sealed Rose forensic engine.

Last Audit: September 2026·Test Corpus: 25,000+ Sampled Frames·Audited by: Kinetic Helix LLC
Section 01 · Forensic Philosophy

Explainable, Calibrated Outcomes vs. Binary Verdicts

A categorical “100% Real” verdict overstates what digital forensics can mathematically prove. Clean media simply indicates an absence of synthetic diffusion signatures, face-swap warp boundaries, or spectral phase anomalies. Sealed Rose employs calibrated probabilistic outcomes:

Passed Optical Check

No strong synthetic-media or face-swap signals detected across sampled frames. Optical camera noise and EXIF structures align with physical capture.

Inconclusive Result

Insufficient resolution, extreme compression blur, or ambiguous feature boundaries. Neither confirmed synthetic nor certified authentic.

Likely AI-Generated

Elevated spatial diffusion artifacts, latent Fourier spectral anomalies, or neural facial warping detected with calibrated certainty score.

Section 02 · The 99.4% Accuracy Benchmark

Benchmark Corpus, Class Balance & Test Environments

The platform’s 99.4% benchmark accuracy metric represents holistic evaluation across standardized academic benchmarks alongside proprietary contemporary generative media test sets:

Benchmark / DatasetEvaluation ScopeSample SizeAccuracy
FaceForensics++ (c23 / c40)Deepfakes, Face2Face, FaceSwap, NeuralTextures8,400 clips99.5%
DFDC (Deepfake Detection Challenge)Multi-actor, variable lighting, real-world compression10,200 clips98.9%
Celeb-DF v2High-visual-quality celebrity face-swaps3,200 clips99.4%
Diffusion Synthesis Suite 2026Flux.1, Midjourney v6, SDXL, Sora, Wan 2.1, Kling 1.55,000 images/vids99.7%

Class Balance: Testing maintains a strict 50% authentic (raw camera files, validated optical archives) and 50% synthetic/manipulated split to eliminate prevalence skew.

Section 03 · Empirical Error Rates & Performance

False Positives, False Negatives & Latency Profiles

False Positive Rate

0.58%

Real optical photos or authentic videos misidentified as AI. Most frequently caused by aggressive beauty filters or heavy HDR post-processing.

False Negative Rate

1.18%

Synthetic media escaping detection. Primarily observed on low-resolution files subjected to multi-generation re-encoding (e.g., 5th-generation WhatsApp forwards).

Inference Latency

<450 ms

Average single-frame image inference. Multi-frame video decomposition completes in 1.8–3.4s across 10–45 sampled frames.

Section 04 · Boundaries & Supported Scenarios

Forensic Limitations & Unsupported Use Cases

Transparency regarding model limits is critical for investigators, journalists, and legal counsel:

Low-Resolution Media (<256×256 px)

When pixel dimensions fall below 256px, high-frequency spatial Fourier artifacts and latent diffusion residuals are severely attenuated. The scanner triggers an “Inconclusive” verdict rather than providing an ungrounded binary claim.

Multi-Generation Social Compression

Videos downloaded and re-uploaded across multiple platforms (e.g., TikTok → Instagram → WhatsApp → Reddit) undergo destructive lossy quantization (macroblocking), masking subtle generative boundary artifacts.

Heavy Face Occlusion (<15% Bounding Box)

Deepfake face-swap models require sufficient unobstructed facial landmarks. If a subject’s face occupies under 15% of the frame or is obscured by masks or extreme lighting, landmark mesh tracking becomes unviable.

Non-Photorealistic Stylized Art

Hand-drawn illustrations, vector art, 3D animated renders, and anime styles exhibit intentional artificial line geometries and flat color spaces that can confuse natural optical sensors.

Section 05 · Architectural Privacy

Multi-Tier Data Retention Architecture

Sealed Rose strictly maintains separate technical boundaries between volatile computational memory, temporary queues, cryptographic telemetry, and statutory records:

0 Bytes Storage

Raw Verification Media (RAM Ephemeral)

User uploads exist exclusively in volatile RAM during active neural inference. Raw bytes are freed immediately upon response transmission and are never persisted to disk.

24–48h Cache

Asynchronous Pipeline Scratch Buffers

Temporary stream chunks generated during cloud video resolution or recovery retry pipelines are held in encrypted transient buffers and automatically purged within 24 to 48 hours.

Cryptographic Log

One-Way SHA-256 Hashes & Quota Counters

Irreversible cryptographic SHA-256 hashes and timestamp counters are logged in our PostgreSQL database to enforce 24-hour daily free quotas and support verifiable audit certificates.

7-Year Ledger

Stripe Invoices & Financial Ledgers

Transaction IDs, payment timestamps, and credit minting events are preserved for 7 years to satisfy federal/state corporate tax and AML statutory audit requirements.

Corporate Accountability

Operated by Kinetic Helix LLC

Sealed Rose is a registered brand operated by Kinetic Helix LLC, a limited liability company organized under the laws of the State of Florida, United States.

JurisdictionFlorida, USA
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