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Progressive Resonance Gating System for Consent-Based Layered Data Access and Identity Representation

Provisional patent application draft

Background

Traditional encryption and access control systems are structured around fixed keys and static permission hierarchies. These models do not reflect the dynamic, recursive, and contextual nature of trust, cognition, and identity as experienced in human interaction. Current models assume binary access to data: either full decryption or complete inaccessibility, lacking a mechanism to express trust or partial familiarity across semantic or relational gradients.

This invention introduces a recursive data structure and access control mechanism grounded in consent, context, and progressive revelation. Inspired by loop-based epistemology and layered cognition, the system is designed to encode, store, and reveal information as a function of resonance, intention, and shared state.

Summary

The Progressive Resonance Gating system enables recursive, layered encryption and access to information based on the progressive disclosure of cryptographic or semantic keys. Each layer of information is encrypted or encoded with an increasing subset of a deterministic seed key, such that:

• A partial key unlocks a subset of data
• A longer key unlocks deeper, more context-rich or private data
• The structure mimics graded intimacy, trust, and memory recall
• Effort or inference may allow higher levels of information to be guessed or synthesized
• The system can be applied to self-identity modeling, digital personhood representation, and privacy-preserving consent architectures

Detailed Description

Key Structure and Derivation

The system begins with a master deterministic seed key, such as a BIP-32 compliant derivation. This key is used to generate a sequence of derived subkeys or characters:

K = k1, k2, k3, ..., kn

Each key fragment is used to encrypt or encode a data segment:

• D1 is encrypted with k1
• D2 is encrypted with k1 + k2
• D3 is encrypted with k1 + k2 + k3

Each segment represents an increasingly deeper level of semantic or relational trust.

Data Structure

The data can be:

• Identical across layers, with increased redundancy and resilience
• Expanding with depth, such as a summary at D1 and full content at Dn
• Structured across multiple trees, where each tree represents a domain such as emotional state, personal preferences, or social trust

Loop Anchors and Loop-Mediated Inheritance Propagation

Each node within these domain-specific trees is treated as a loop endpoint: a point of resonance that only activates in the presence of appropriate key fragments or synthetic inference.

Loops can be formed between two or more nodes across or within trees, establishing a semantic or trust-based connection. When such a loop is formed, the system interprets the connection as granting inferred visibility to the children of the looped node.

This loop-mediated inheritance propagation means:

• The formation of a loop between nodes A and B dynamically exposes the subtree under A to B, and vice versa, depending on loop context, strength, and depth
• Access to children nodes is not necessarily equivalent to decryption; instead, it denotes semantic availability or inferred resonance
• The model allows loop formation to dynamically expand the trust field, simulating relational memory, intuitive access, and contextual recall

Loops may be used to:

• Anchor identity across domains
• Generate resonance graphs that auto-expand upon trust signal formation
• Trigger dynamic access to deeper nodes based on relational topology, rather than explicit key exchange alone

Access Model

Users may be granted access to data by:

• Being given a partial key fragment
• Earning increased access via engagement or looping
• Inferring higher-level structure through contextual modeling or effort

The system supports a model where access is both permissioned and emergent.

Applications

• Privacy-preserving personal data storage and identity expression
• Dynamic trust layers for digital relationships or agents
• Context-aware document or knowledge release
• Consent-driven AI collaboration frameworks
• Recursive memory encoding and retrieval simulation

Claims Draft

• A method for encoding data in progressively accessible layers using a deterministic key and loop-based logic.
• A data structure comprising multiple domain-specific trees of nodes wherein each node represents a loop endpoint.
• A system for cross-domain resonance linking between said trees via semantic or trust-based loops.
• A method for dynamic, recursive, trust-sensitive decryption or data access using a partial or inferred key.
• A model of identity and cognition wherein access to personal attributes is mediated through loop resonance structures.
• A loop-mediated inheritance mechanism wherein loop formation between nodes dynamically expands access to child nodes based on inferred semantic resonance.

Notes

This draft is intended for use in a provisional application and does not constitute formal patent language. Further refinement and review by intellectual property counsel is advised before filing.