A quantum-resistant protocol for cyber offense/defense, grounded in wavelet-based steganography, multi-layer obfuscation, PQC encryption, and high-ratio compression. It integrates into a multi-product framework (DDTP-Offense for progressive unpacking/malware in videos; DDTP-Defense for C2 obfuscation/images in low-resource ops; DDTP-Cloud for dataset chunking/fractals, reducing storage from 90 PB to 1-2 PB). Prioritizes video for high capacity (up to 8 bpp/frame, ~0.58 GB/10s video) on GPUs; images for speed (<1s, ~1 MB) on CPUs, with resource-aware selection.
Key Specifications:
Embedding: 2-5 layers; DWT on video frames (first layer max density, higher for obfuscation); fractal/AI patterns; 2D methods for compatibility.
Compression/Security: DWT/Haar wavelets for 50-100:1 ratios; PQC (ML-KEM/HQC) + AES-256; FEC for inter-layer resilience.
Performance: <10s/116 MB; benchmarks show 600 MB in 10s videos vs. 1 MB images; AI for carrier selection (video for capacity, images for speed).
Networking: Supports distributed setups; integrates with DoD networks.
Hardware Modifications: Adaptive for legacy/CPU-only; GPU offload for parallel processing.
Use Cases: Cyber offense (self-replication in social media); defense (zero-trust C2); cloud (large dataset compression/archival).
Platform Support: On-prem/hybrid; Python-based microservices; integrates with AWS/Azure/GCP.
A quantum-resistant protocol for cyber offense/defense, grounded in wavelet-based steganography, multi-layer obfuscation, PQC encryption, and high-ratio compression. It integrates into a multi-product framework (DDTP-Offense for progressive unpacking/malware in videos; DDTP-Defense for C2 obfuscation/images in low-resource ops; DDTP-Cloud for dataset chunking/fractals, reducing storage from 90 PB to 1-2 PB). Prioritizes video for high capacity (up to 8 bpp/frame, ~0.58 GB/10s video) on GPUs; images for speed (<1s, ~1 MB) on CPUs, with resource-aware selection.
Key Specifications:
Embedding: 2-5 layers; DWT on video frames (first layer max density, higher for obfuscation); fractal/AI patterns; 2D methods for compatibility.
Compression/Security: DWT/Haar wavelets for 50-100:1 ratios; PQC (ML-KEM/HQC) + AES-256; FEC for inter-layer resilience.
Performance: <10s/116 MB; benchmarks show 600 MB in 10s videos vs. 1 MB images; AI for carrier selection (video for capacity, images for speed).
Networking: Supports distributed setups; integrates with DoD networks.
Hardware Modifications: Adaptive for legacy/CPU-only; GPU offload for parallel processing.
Use Cases: Cyber offense (self-replication in social media); defense (zero-trust C2); cloud (large dataset compression/archival).
Platform Support: On-prem/hybrid; Python-based microservices; integrates with AWS/Azure/GCP.
