InterID: Cross-Ecosystem & AR Identity

• InterID is a unified set of systems and protocols that enable secure identity verification and management across digital, governmental, and AR-driven environments.
• Its architecture employs modular layers, adapter patterns, and standardized APIs to facilitate interoperability among diverse identity ecosystems.
• InterID utilizes advanced cryptographic methods, zero-knowledge proofs, and federated trust models to ensure privacy, scalability, and robust user verification.

InterID encompasses a set of technical systems, protocols, and methodologies unified by the goal of enabling identity management, user verification, or person re-identification across ecosystem, organizational, or national boundaries. This term is used in both digital identity interoperability (notably for cross-ecosystem and cross-border government or blockchain systems) and person-centric recognition frameworks (notably in AR/egocentric and Re-ID contexts). Modern InterID implementations are built on principles such as self-sovereign identity, distributed trust anchors, interoperability layers, and modular extensibility. This article summarizes the principal architectures, protocols, trust and governance models, technical stacks, and application domains of InterID, referencing canonical systems and frameworks in current literature.

1. InterID for Cross-Ecosystem and Cross-Border Digital Identity

InterID in digital identity contexts refers to the creation of interoperable frameworks for verifying user credentials and identities between otherwise isolated identity ecosystems or governmental foundational ID registries. Key motivating factors include technological heterogeneity, regulatory divergence, and the need for trust alignment between disparate actors (Yildiz et al., 29 Dec 2025, Ibor et al., 2023).

1.1. Self-sovereign and Federated Identity Orchestration

Modern systems such as "interID – An Ecosystem-agnostic Verifier Application for Self-sovereign Identity" provide a unified REST API and orchestration middleware that bridges distinct self-sovereign identity (SSI) backends (Hyperledger Indy/Aries, EBSI, EUDI). This is achieved through:

• Three-layered architecture: (a) Presentation/UI for template and credential interaction, (b) Controller Layer for orchestration and session management, (c) Service Layer comprising ecosystem-specific adapter modules and verifier backends.
• Ecosystem-agnostic API abstraction: A single set of endpoints (/proof-templates, /proof-requests) that masks protocol details, enabling service providers to seamlessly initiate and verify proofs without ecosystem-specific logic (Yildiz et al., 29 Dec 2025).
• Adapter pattern for extensibility: Each ecosystem integrates via a standardized adapter interface, making the addition of new ecosystems modular.

1.2. Cross-Border Governmental Identity Frameworks

Architectures such as the one described in "Trustworthy Cross-Border Interoperable Identity System for Developing Countries" propose federated, trust-anchored interoperability fabrics that link national foundational ID systems through:

• Interoperable Layer: Enforces data representation, semantic agreement (e.g., JSON-LD/W3C VC), subject binding via cryptography, and security/privacy conformance (TLS, SAML, consent management).
• Trust-Scoring Models: Weighted metrics of security, privacy, and compliance; trust scores are updated dynamically with transaction experience.
• Consent and Privacy Enforcement: Mandatory consent logs, pseudonymization, and privacy impact/risk assessments conforming to standards (ISO 29134).
• Standardized Protocol Stack: X-Road, SAML, OAuth2/OIDC, Verifiable Credentials; mutual recognition treaties and technical conformance as trust/gatekeeping mechanisms (Ibor et al., 2023).

1.3. Distributed Identity Management for DLT Interoperation

In the blockchain/enterprise setting, InterID refers to decentralized identity management schemes facilitating secure authentication and credential exchange between permissioned ledger networks:

• Identity Plane: Distributed cloud of Interoperation Identity Networks (IINs) built on permissioned ledgers (e.g., Hyperledger Indy), storing DIDs, VCs, revocation registries.
• Data Plane: Each participating organization runs an IIN Agent, registers DIDs, maintains membership VCs, verifies peer credentials via zero-knowledge proofs, and triggers chaincode updates for secure on-chain proof validation.
• Cryptographic Foundations: Camenisch–Lysyanskaya signatures, cryptographic accumulators for revocation, CL-based zero-knowledge proofs for privacy-preserving verification.
• Performance Characteristics: End-to-end identity sync per foreign org is ≈600–800 ms; ZK proof generation ≈150–250 ms; system impact on data-plane throughput negligible (<5% reduction) (Ghosh et al., 2021).

2. Core Technical Components and Protocol Flows

2.1. Modular Verification and Credential Exchange

Layer	Role	Technologies/Protocols
Presentation	UI, template creation	React, REST, QR, Deeplinks
Controller	API orchestration, session mgmt	Node.js, Redis, Mongoose
Service (Adapters)	Ecosystem native interaction	Dockerized backends, Adapter

(Yildiz et al., 29 Dec 2025)

All ecosystem-specific proof request/response cycles are abstracted into the following canonical adapter interface:

• generateProofRequest(templateSection, sessionId) → Invitation URL, DeepLink, QR
• handleCallback(callbackPayload) → Standardized verification result

2.2. Protocols for Trust, Security, Privacy

• Authentication/Authorization: SAML 2.0/TLS, OAuth2.0, mutual TLS, on-chain certificate proofs
• Cryptographic Binding: ECDSA/RSA signatures, CL ZK proofs, cryptographic accumulators
• Consent Enactment: Explicit consent logs, data minimization, audit trails

System-specific security analysis ensures (a) strong cryptographic soundness, (b) privacy-by-design via ZK proofs, (c) non-repudiation, (d) no central points of trust (Ghosh et al., 2021, Yildiz et al., 29 Dec 2025, Ibor et al., 2023).

2.3. Data and Trust Models

• Verifiable Credentials: JSON-LD attribute statements, CL signatures, revocation registries with acc/witness protocols.
• Governance and Trust Anchors: Multi-layer governance stack (legal recognition, technical certification, trust score thresholding).
• Dynamic Trust Update: $$T_{ij}(t+1) = \lambda\,T_{ij}(t) + (1–\lambda)\,E_{ij}(t)$$ (Ibor et al., 2023).

3. Performance, Extensibility, and Deployment Characteristics

• Overhead: Absolute verification latency remains interactive (10–150 ms typical); marginal overheads exist for orchestration layers (e.g., 13–61% depending on ecosystem), but do not exceed 0.1–0.2 s in real flows (Yildiz et al., 29 Dec 2025).
• Plugin Integration: New ecosystems added by Dockerizing backends, exposing endpoint configs, implementing adapters; frontend agnostic except for option registration.
• Scalability: Distributed consensus (RBFT) on ledger, peer-to-peer DIDComm, per-network certification, member discovery.
• Real-World Deployments: Used in eGovernment, SSI pilots, multi-ledger blockchain consortia.

4. InterID in Person-Centric and Egocentric Recognition

InterID is also applied to unobtrusive user identification in AR and egocentric environments, focusing on person recognition from human-object interaction signatures rather than conventional digital credentials.

4.1. Egocentric Human-Object Interaction Identification

• I2S (Interact2Sign) Framework: Three-stage sequential Bayesian classifier pipeline: (1) object ID, (2) human-object interaction, and (3) user identification, each informed by handcrafted 3D hand pose descriptors (spatial, orientation, kinematic, frequency, inter-hand envelope).
• Feature Engineering: Multi-dimensional descriptors (e.g., 688D spatial, 144D orientation) are aggregated with dispersion- and range-aware statistics.
• Classifier Ensemble: All stages use XGBoost; full system achieves F1-score 97.52%, user F1 99.56%, real-time (<0.1 s), lightweight (<4 MB) (Hamza et al., 20 Sep 2025).

4.2. Robustness and Deployment

• Model Size and Latency: Model <4 MB; inference time <0.1 s; consistent per-user identification >99.3% F1.
• Deployment Contexts: Designed for AR-based assistive/secure systems, e.g., cockpit authentication, maintenance, surgical workflow (Hamza et al., 20 Sep 2025).

5. Challenges, Limitations, and Future Directions

5.1. Interoperability, Governance, and Trust

• Challenges: Institutional trust deficits, vendor lock-in, lack of standards, legislative asymmetries, infrastructure gaps, and privacy concerns.
• Remediation: Open standards, semantic alignment (W3C/JSON-LD), model legal frameworks, and consent-driven architectures are prescribed (Ibor et al., 2023).

5.2. Performance and Privacy Tradeoffs

• Performance Bottlenecks: ZK proof generation and ledger synchronization are sub-second but require optimization for mass deployment.
• Privacy vs. Audit: Blockchain-based audit logs provide transparency but increase the risk of linkability; selective disclosure (BBS+, ZK-SNARKs) is essential (Ghosh et al., 2021).

5.3. Future Work

• Broader ecosystem integration: Extending plugin architectures for emerging SSI and identity platforms (Yildiz et al., 29 Dec 2025).
• Advanced cryptography: Introduction of more efficient ZK proof systems and privacy-preserving analytics.
• In egocentric domains: Expansion to multimodal features (gait, voice), semi-supervised adaptation, and more complex, in-situ authentication pipelines (Hamza et al., 20 Sep 2025).

6. Summary Table: Canonical InterID Systems

System	Domain	Main Purpose	Key Technologies
interID (Yildiz et al., 29 Dec 2025)	Digital ID SSI	Cross-ecosystem credential verify	REST API, adapters, Docker, HC/Aries/EBSI/EUDI
X-border InterID (Ibor et al., 2023)	e-Gov/FIDS	Pan-national trusted ID	eIDAS, SAML, OAuth2, X-Road, VCs
DLT InterID (Ghosh et al., 2021)	Blockchain	Distributed identity across ledgers	Indy, Aries, DIDs, CL-ZK proofs
I2S InterID (Hamza et al., 20 Sep 2025)	AR/Egocentric	User ID from hand-object interaction	3D pose, XGBoost, multi-stage

These systems collectively illustrate the broad spectrum of contemporary InterID: standards-based cross-ecosystem digital identity verification, federated government eID trust fabrics, distributed ledger mutual credentialing, and wearable context-driven unobtrusive person recognition.