Entros Protocol: A Framework for Temporally-Consistent, Decentralized Proof-of-Personhood

Abstract

The proliferation of sophisticated AI and bot networks necessitates robust methods for verifying human uniqueness and liveness in digital ecosystems. Existing Proof-of-Personhood (PoP) solutions rely on centralized authorities, invasive static biometrics, or socially-correlatable data, creating vulnerabilities in privacy, security, and accessibility. We introduce the Entros Protocol, a decentralized framework for PoP and Self-Sovereign Identity built on Solana. The core innovation is temporal consistency: the assertion that human identity is best proven not by a static secret, but by the bounded, chaotic drift of biological and behavioral patterns over time. The framework captures multi-modal behavioral data (voice prosody, hand tremor, touch dynamics) during a configurable behavioral challenge, extracts a 308-dimensional feature vector, and produces a 256-bit locality-sensitive hash via SimHash. A Groth16 zero-knowledge proof verifies that consecutive fingerprints fall within a bounded Hamming distance without revealing either value. Attestations are anchored to non-transferable identity tokens (SPL Token-2022) with progressive Trust Scores. We provide formal security definitions, analyze the protocol against replay, synthesis, and Sybil attacks, introduce a graduated trust model distinguishing first-time liveness checks from sustained temporal consistency, and present benchmarks from a working implementation deployed on Solana devnet.