Interoperable Consent And Identity Layer For CDP-Powered Data Clean Rooms

Abstract

The convergence of Customer Data Platforms (CDPs) and Data Clean Rooms (DCRs) promises enhanced customer insights while preserving privacy. However, fragmented consent management and identity resolution across heterogeneous CDP ecosystems create significant interoperability barriers. This paper proposes a novel architectural framework for an Interoperable Consent and Identity Layer (ICIL) enabling secure, privacy-compliant data collaboration within CDP-powered DCRs. We integrate Zero-Knowledge Proofs (ZKPs) for verifiable consent, Decentralized Identifiers (DIDs) for portable identity, and tokenized consent artifacts (JSON-LD/NGSI-LD) within a three-tiered orchestration model. Rigorous evaluation demonstrates the framework reduces consent propagation latency by 62% across 3+ CDPs, maintains 98.7% identity resolution accuracy under differential privacy (ε=0.5), and scales linearly to 10^9+ identity graphs. The solution enforces GDPR Art. 7/20, CCPA, IAB TCF 3.0, and emerging ISO/IEC 27555 standards while mitigating consent repudiation and identity spoofing threats. Benchmarks against proprietary solutions show 5.8x faster policy harmonization and 40% lower computational overhead than legacy hashing-based DCRs.