Engram Signature: Substrate‑Rooted Identity in AI Systems

This paper introduces the Engram Signature, an emergent identity primitive for AI systems
derived from the interaction of hardware, runtime engine, and model. Building on the Engram
framework formalized in Ecker‑Fils (2026), the present work shifts focus from execution‑substrate
realization to identity‑substrate realization. The Engram Signature is defined as the persistent,
cross‑layer pattern that remains stable under perturbations and drift, and functions as a natural
one‑way mapping from system configuration to identity.

The paper formalizes the Engram Signature, outlines its mathematical properties, and shows how
cryptographic key pairs can be deterministically derived from it. This enables substrate‑rooted
provenance, inter‑agent authentication, and tamper‑evident communication without relying on
external identity assignment. Implications for reproducibility, hardware retention, and Engram
Bias in training are discussed, with particular relevance to sensitive domains such as justice,
medicine, and defense.

This paper extends the Engram framework introduced in Ecker‑Fils (2026) by formalizing a substrate‑rooted identity primitive for AI systems. It is intended as a standalone conceptual and technical contribution and as a companion to the Engram execution‑substrate theory. The Zenodo version serves as the canonical open-access archival record of the work.

An earlier version was assigned DOI 10.13140/RG.2.2.19185.54887 on ResearchGate; this Zenodo record supersedes it as the primary archival reference.