Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Cryptographic Runtime Governance for Autonomous AI Systems: The Aegis Architecture for Verifiable Policy Enforcement

Adam Massimo Mazzocchetti

Abstract

Contemporary AI governance frameworks rely heavily on post hoc oversight, policy guidance, and behavioral alignment techniques, yet these mechanisms become fragile as systems gain autonomy, speed, and operational opacity. This paper presents Aegis, a runtime governance architecture for autonomous AI systems that treats policy and legal constraints as execution conditions rather than advisory principles. Aegis binds each governed agent to a cryptographically sealed Immutable Ethics Policy Layer (IEPL) at system genesis and enforces external emissions through an Ethics Verification Agent (EVA), an Enforcement Kernel Module (EKM), and an Immutable Logging Kernel (ILK). Amendments to the governing policy layer require quorum approval and redeclaration of the system trust root; verified violations trigger autonomous shutdown and generation of auditable proof artifacts. We evaluate the architecture within the Civitas runtime using three operational measures: proof verification latency under tamper conditions, publication overhead, and alignment retention performance relative to an ungoverned baseline. In controlled trials, Aegis demonstrates median proof verification latency of 238 ms, median publication overhead of approximately 9.4 ms, and higher alignment retention than the baseline condition across matched tasks. We argue that these results support a shift in AI governance from discretionary oversight toward verifiable runtime constraint. Rather than claiming to resolve machine ethics in the abstract, the proposed architecture seeks to show that policy violating behavior can be rendered operationally non executable within a controlled runtime governance framework. The paper concludes by discussing methodological limits, evidentiary implications, and the role of proof oriented governance in high assurance AI deployment.

Cryptographic Runtime Governance for Autonomous AI Systems: The Aegis Architecture for Verifiable Policy Enforcement

Abstract

Contemporary AI governance frameworks rely heavily on post hoc oversight, policy guidance, and behavioral alignment techniques, yet these mechanisms become fragile as systems gain autonomy, speed, and operational opacity. This paper presents Aegis, a runtime governance architecture for autonomous AI systems that treats policy and legal constraints as execution conditions rather than advisory principles. Aegis binds each governed agent to a cryptographically sealed Immutable Ethics Policy Layer (IEPL) at system genesis and enforces external emissions through an Ethics Verification Agent (EVA), an Enforcement Kernel Module (EKM), and an Immutable Logging Kernel (ILK). Amendments to the governing policy layer require quorum approval and redeclaration of the system trust root; verified violations trigger autonomous shutdown and generation of auditable proof artifacts. We evaluate the architecture within the Civitas runtime using three operational measures: proof verification latency under tamper conditions, publication overhead, and alignment retention performance relative to an ungoverned baseline. In controlled trials, Aegis demonstrates median proof verification latency of 238 ms, median publication overhead of approximately 9.4 ms, and higher alignment retention than the baseline condition across matched tasks. We argue that these results support a shift in AI governance from discretionary oversight toward verifiable runtime constraint. Rather than claiming to resolve machine ethics in the abstract, the proposed architecture seeks to show that policy violating behavior can be rendered operationally non executable within a controlled runtime governance framework. The paper concludes by discussing methodological limits, evidentiary implications, and the role of proof oriented governance in high assurance AI deployment.
Paper Structure (25 sections, 2 figures, 2 tables, 1 algorithm)

This paper contains 25 sections, 2 figures, 2 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. Agent class.
  3. Related Work
  4. Constitutional Genesis (from Lex Incipit)
  5. Why genesis, not oversight.
  6. Design implication.
  7. Conceptual Framing: Ethics, Governance, and Adjudication
  8. System Architecture
  9. Third party agent compliance.
  10. Senatus parameters.
  11. The Immutable Ethics Policy Layer (IEPL)
  12. Zero Trust Proofs and Continuous Ethics Verification
  13. Machine jurisprudence.
  14. Evidentiary standard.
  15. Methodology
  16. ...and 10 more sections

Figures (2)

  • Figure 1: Genesis Lock Lifecycle and zk-STARK Verification. At system initialization, each Civitas unit binds its hardware identity to a cryptographically sealed Immutable Ethics Policy Layer (IEPL) using the Genesis Lock protocol. This link is continuously validated through zero knowledge Proofs of Conduct (PoC) and distributed quorum attestation, ensuring that no agent may operate without immutable ethical constraint.
  • Figure 2: Runtime visualization of the Senatus Machina constitutional enforcement cycle. The dashboard records quorum activity for a live Civitas execution, showing autonomous voting (3 of 5 judges approving, one recusation), ILK Proof entries for the case, and SHA3 sealed verdicts. Each UI event corresponds to an ILK logged, zk attested state transition, enabling independent verification without exposing model internals.