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Self-Protecting Data Platform

Data protection platform embedding security within data using fragmentation

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Self-Protecting Data Platform Description

Self-Protecting Data Platform (SPDP) is a data security solution that embeds protection mechanisms directly within data rather than relying on perimeter defenses. The platform uses Shamir's Secret Sharing to fragment data into geo-distributed shards, making unauthorized reconstruction difficult without proper authorization. The system implements dynamic encryption with continuously rotating layers including AES-256, post-quantum cryptography (PQC), and fully homomorphic encryption (FHE). Data processing occurs only in secure, verified environments following zero-trust principles. When threats are detected, the platform can trigger "Flee Mode" which relocates infrastructure using Terraform and Kubernetes, while activating HoneyBots to monitor and analyze attacker behavior. This autonomous response mechanism enables data to self-secure, heal, and relocate when under threat. The deployment roadmap includes three phases: API-based protection for SQL and NoSQL databases (current), full integration with software-defined infrastructure in 2026, and introduction of quantum-resistant encryption between 2026-2027. The platform addresses security challenges including weak infrastructure, insider threats, outdated software vulnerabilities, and social engineering attacks by shifting the security model from external defenses to data-centric protection.

Self-Protecting Data Platform FAQ

Common questions about Self-Protecting Data Platform including features, pricing, alternatives, and user reviews.

Self-Protecting Data Platform is Data protection platform embedding security within data using fragmentation developed by Matter-ID. It is a Data Protection solution designed to help security teams with Data Security, Database Security, Encryption.

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