Patent 10984445

Derivative works

Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.

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Derivative works

Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.

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As a Senior Patent Strategist and Research Engineer specializing in Defensive Publishing, I have analyzed the core claims of U.S. Patent 10,984,445. The following document is a defensive disclosure of derivative inventions and technical variations. The purpose of this disclosure, dated April 29, 2026, is to place these concepts in the public domain, thereby creating prior art to preclude patenting of these and similar incremental improvements by third parties.

The core concept analyzed is a system wherein a central Profile Owner computer receives user profiles from Profile Suppliers, matches these profiles against requests from Media Property entities, and arranges for the user to be tagged such that the selected Media Property can read the tag, access the profile, and deliver a targeted advertisement.

Defensive Disclosure: Derivative Embodiments and Applications

1. Material & Component Substitution

These variations substitute core data structures, protocols, and system components of the claimed invention to achieve the same functional outcome.

1.1. Derivative: Cryptographic & Hardware-Based Tagging

  • Enabling Description: This variation replaces the standard cookie or device ID "tag" with a cryptographically secure, time-limited identifier. The Profile Owner computer, upon matching a visitor profile to a Media Property request, generates a JSON Web Token (JWT). This JWT contains claims identifying the visitor's profile category (e.g., "interest": "automotive") and the intended Media Property audience ("aud": "media-property-domain.com"). The token is signed with the Profile Owner's private key. The Profile Owner arranges for this JWT to be stored on the visitor device (e.g., in localStorage). When the visitor accesses the Media Property, the Media Property's system retrieves the JWT, verifies its signature using the Profile Owner's public key, and extracts the profile claims to deliver the ad. A further enhancement uses a hardware-based identifier from a device's Trusted Execution Environment (TEE), such as Apple's Secure Enclave ID or an Android StrongBox Keystore attestation key, as the core visitor identifier to which the profile is linked, preventing tag spoofing.

  • Mermaid Diagram:

    sequenceDiagram
    participant V as Visitor Device
    participant PS as Profile Supplier
    participant PO as Profile Owner
    participant MP as Media Property

    V->>+PS: Visits site
    PS->>+PO: Redirects with profile data
    PO-->>-PS: Acknowledges
    PO->>PO: Matches profile to MP's request
    PO->>V: Issues signed JWT (Tag)
    Note over V: Stores JWT in localStorage
    V->>+MP: Later visits Media Property
    MP->>V: Reads JWT from localStorage
    MP->>MP: Verifies JWT signature
    MP->>V: Delivers targeted advertisement

1.2. Derivative: Distributed Ledger for Profile & Request Registry

  • Enabling Description: The central database is replaced with a permissioned distributed ledger (e.g., Hyperledger Fabric). Each Media Property's profile request is recorded as a transaction on the ledger, creating an immutable record. When a Profile Supplier provides a new visitor profile, the Profile Owner computer hashes the profile attributes and checks the ledger for matching request hashes. Upon a match, the Profile Owner initiates a smart contract that records the profile-to-Media-Property link. The "tag" stored on the visitor's device is a pointer to this transaction record on the ledger. This architecture provides a verifiable, auditable trail of data sharing, useful for royalty calculations and privacy compliance.

  • Mermaid Diagram:

    flowchart TD
    subgraph Visitor Device
        A[Tag: Transaction ID]
    end
    subgraph Profile Owner System
        B[Profile Ingestion Module]
        C[Smart Contract Executor]
        D[Hashing Engine]
    end
    subgraph Distributed Ledger
        E[Block 1: MP_A requests "travel"]
        F[Block 2: MP_B requests "auto"]
        G[Block N: Visitor_XYZ matched to MP_A]
    end
    H[Profile Supplier] -- Profile Data --> B
    B -- Profile Attributes --> D
    D -- Hashed Profile --> C
    C -- Reads Requests --> E & F
    C -- Writes Match --> G
    C -- Returns Tx ID --> A

2. Operational Parameter Expansion

These variations describe the core invention operating at extreme scales and frequencies.

2.1. Derivative: High-Frequency Trading (HFT) Signal Distribution

  • Enabling Description: The invention is adapted for microsecond-latency financial markets. The "Profile Suppliers" are real-time natural language processing (NLP) engines that scan news feeds and social media, generating sentiment profiles (e.g., "bullish on AAPL"). The "Profile Owner" is a central market data hub. "Media Properties" are algorithmic trading engines that have submitted standing requests for specific sentiment profiles related to certain equities. When a new sentiment profile is generated, the hub matches it to a trading engine's request. The "tagging" is a direct memory access (DMA) write over a 100GbE network connection to a specific memory address on the trading engine's server, and the "advertisement" is the sentiment data payload itself, which triggers a trade execution within nanoseconds.

  • Mermaid Diagram:

    graph LR
    A[News Feed NLP Engine] -- Sentiment Profile --> B(Central Data Hub);
    C[Algo Trading Engine] -- Request: 'bullish on AAPL' --> B;
    B -- Matches Profile to Request --> D{DMA Write};
    D -- Payload Delivered --> C;
    C -- Triggers --> E[Trade Execution];

2.2. Derivative: National-Scale Utility Grid Load Balancing

  • Enabling Description: The system manages energy distribution across a national power grid. "Profile Suppliers" are millions of smart meters in homes and businesses, reporting real-time consumption data. A "profile" is an aggregated pattern indicating, for instance, a surge in EV charging in a specific region. The "Profile Owner" is the national grid operator's central control system. "Media Properties" are power generation facilities (hydro, solar, gas) that have submitted requests to be notified of demand profiles they are best suited to meet. Upon detecting a regional demand profile, the operator's system tags the profile and provides it to the selected power plant. The "advertisement" is a power generation ramp-up command sent to that facility.

  • Mermaid Diagram:

    stateDiagram-v2
    [*] --> Idle
    Idle --> Analyzing: Smart meter data received
    Analyzing --> Matched: Demand profile (EV charging surge) matches hydro plant's capacity request
    Matched --> Commanding: Send "increase generation" command to hydro plant
    Commanding --> Idle: Command acknowledged

3. Cross-Domain Application

These variations apply the core mechanism to disparate industries.

3.1. Derivative: Aerospace - Autonomous Satellite Debris Avoidance

  • Enabling Description: The system functions as a decentralized space traffic management network. "Profile Suppliers" are ground-based observatories and in-orbit sensors that detect and characterize space debris, generating a state vector profile (position, velocity, size). The "Profile Owner" is a federated data hub for space situational awareness. "Media Properties" are commercial satellite operators who have filed "requests" for profiles of any object predicted to pass within a certain threshold of their assets. When a new debris profile matches a satellite's keep-out zone, the hub tags the debris profile and provides it to the satellite's flight control system. The "advertisement" is a recommended collision avoidance maneuver plan.

  • Mermaid Diagram:

    sequenceDiagram
    participant Sensor as Debris Sensor
    participant Hub as Federated Data Hub
    participant SatFC as Satellite Flight Control
    Sensor->>Hub: Reports Debris Profile (State Vector)
    Hub->>Hub: Compares profile against satellite keep-out zones (Requests)
    Hub->>SatFC: Provides matched debris profile
    SatFC->>SatFC: Calculates avoidance maneuver

3.2. Derivative: AgTech - Precision Pest Management

  • Enabling Description: The system is used for targeted agricultural intervention. "Profile Suppliers" are autonomous drones equipped with multispectral cameras that scan fields, identifying specific pest infestations (e.g., spider mites on corn) and creating a geospatial "pest profile." The "Profile Owner" is a central farm management server. "Media Properties" are fleets of automated pesticide-spraying drones that have requested pest profiles matching the specific pesticide they carry. The central server matches the infestation profile to the appropriate spraying drone and provides the location data. The "advertisement" is the mission plan (flight path and spray volume) uploaded to the selected drone for execution.

  • Mermaid Diagram:

    graph TD
    A(Scanning Drone) -- Geospatial Pest Profile --> B{Farm Management Server};
    C(Spraying Drone #1 <br> Carries Miticide) -- Request: 'Spider Mite Profiles' --> B;
    D(Spraying Drone #2 <br> Carries Fungicide) -- Request: 'Fungus Profiles' --> B;
    B -- Matches 'Spider Mite' --> C;
    B -- Provides Mission Plan --> C;
    C --> E(Executes Targeted Spraying);

4. Integration with Emerging Tech

These variations integrate the core patent with AI, IoT, and blockchain.

4.1. Derivative: AI-Driven Predictive Profile Allocation

  • Enabling Description: The Profile Owner computer employs a reinforcement learning (RL) model instead of a simple request-matching engine. The model's state includes the current pool of visitor profiles and available Media Property requests. Its action is to decide which Media Property to provide a given profile to. The reward signal is based on the ultimate conversion rate or revenue generated by the ad served by the Media Property, which is reported back to the Profile Owner. Over time, the RL agent learns to predict which Media Property will make the most effective use of a given profile, even if multiple properties have requested the same profile category. This optimizes the overall network yield beyond simple first-come, first-served matching.

  • Mermaid Diagram:

    flowchart
    A[Visitor Profile Received] --> B{RL Model};
    C[Media Property Requests] --> B;
    B -- Action: Allocate Profile to MP_A --> D[Tagging & Provisioning];
    D --> E[MP_A Serves Ad];
    E -- Conversion Data --> F[Reward Signal Calculation];
    F -- Reward Signal (+/-) --> B;

4.2. Derivative: IoT Predictive Maintenance

  • Enabling Description: The system is applied to an industrial IoT environment. The "visitor device" is a sensor on a factory machine (e.g., a vibration sensor on a motor). The "Profile Supplier" is the local edge computing gateway that processes raw sensor data. It generates a "profile" when the data matches a known pre-failure signature (e.g., high-frequency harmonic vibration). The "Profile Owner" is the central factory operations system. The "Media Properties" are different maintenance teams (electrical, mechanical) who have "requested" to be alerted to specific failure profiles. The system matches the vibration profile to the mechanical team's request, and the "advertisement" is a work order automatically generated in their maintenance scheduling system.

  • Mermaid Diagram:

    sequenceDiagram
    participant Sensor as Machine Sensor
    participant EdgeGW as Edge Gateway
    participant FactoryOps as Factory Operations System
    participant MechTeam as Mechanical Maintenance System

    loop Real-time Monitoring
        Sensor->>EdgeGW: Vibration data stream
    end
    EdgeGW->>EdgeGW: Detects pre-failure signature (Profile)
    EdgeGW->>FactoryOps: Sends Failure Profile
    FactoryOps->>FactoryOps: Matches profile to Mechanical Team's request
    FactoryOps->>MechTeam: Creates "Work Order" (Ad)

5. The "Inverse" or Failure Mode

These variations describe the invention designed for safe failure, privacy, or limited functionality.

5.1. Derivative: k-Anonymity Privacy-Preserving Mode

  • Enabling Description: To comply with strict privacy regulations, the system operates in a low-power, privacy-preserving mode. When the Profile Owner receives a visitor profile, it does not store the individual profile. Instead, it places the visitor into a larger, mathematically-defined cohort of at least 'k' other visitors who share similar attributes (k-anonymity). The "tag" on the visitor's device is the ID for this anonymous cohort. When a Media Property requests a profile, the system does not provide the individual profile but instead confirms that the visitor belongs to a cohort that matches the request. The Media Property can then serve an ad targeted to the cohort (e.g., "males 30-40 interested in travel") without ever knowing the individual's specific data.

  • Mermaid Diagram:

    graph TD
    A[Visitor Profile] --> B{k-Anonymity Engine};
    B -- Assigns Cohort ID --> C(Tag on Visitor Device);
    D[Media Property] -- Requests 'travel' profile --> B;
    B -- Checks Cohort for 'travel' attribute --> D;
    B -- Responds 'Visitor is in Cohort XYZ' --> D;
    D -- Serves Cohort-targeted Ad --> C;

Combination Prior Art with Open-Source Standards

1. Combination with Prebid.js: The Profile Owner's system is implemented as a Real-Time Data (RTD) Provider module within the open-source Prebid.js header bidding framework. When an auction is initiated on a Media Property's website, the Prebid RTD module makes a client-side call to the Profile Owner's API using the visitor's tag. The Profile Owner returns profile data (e.g., ortb2.user.data segments), which Prebid.js automatically appends to the outgoing bid requests to all Demand-Side Platforms (DSPs). This standardizes and decentralizes the profile distribution directly into the programmatic advertising bid stream.

2. Combination with W3C Verifiable Credentials (VCs): The system operates within the W3C's decentralized identity framework. A Profile Supplier acts as a VC "Issuer," cryptographically signing a credential like {"type": "InterestCredential", "interest": "automotive"} and providing it to the visitor, who stores it in their personal "Identity Wallet." The visitor then presents this VC to a Media Property (the "Verifier"). The Media Property, having previously registered its interest in "automotive" profiles with a public Profile Owner "Directory," can verify the credential's authenticity and serve a targeted ad, giving the user direct control over their profile data.

3. Combination with OAuth 2.0 and OpenID Connect: The system is built on the OAuth 2.0 authorization framework. The Profile Owner acts as the Authorization Server. The Profile Supplier, on behalf of the user, initiates an OAuth flow, requesting the user's consent to create a profile. The Profile Owner stores this consent and profile data. When a Media Property (a "Client Application") requires a profile, it initiates a separate OAuth flow. The Profile Owner checks if the user has consented to sharing their profile with this specific Media Property. If so, it issues an access token (the "tag") which the Media Property can use to retrieve the profile claims from a standardized OpenID Connect UserInfo endpoint.

Generated 4/29/2026, 4:53:12 AM