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Distributed AI Accountability Protocol (DAAP) Version 2.0
Internet-Draft E. Aylward Intended status: Informational Aiiva.org Expires: 30 December 2025 30 June 2025 Distributed AI Accountability Protocol (DAAP) Version 2.0 draft-aylward-daap-v2-00 Abstract This document specifies the Distributed AI Accountability Protocol (DAAP) version 2.0, an enhanced framework for authentication, monitoring, and control of autonomous AI agents. DAAP provides cryptographic identity verification, periodic check-ins, remote shutdown capabilities, adaptive location reporting, and behavioral monitoring. The protocol addresses critical challenges in AI safety including accountability gaps, rogue AI risks, and regulatory compliance through a multi-layered approach combining hardware-backed security, real-time monitoring, and ethical governance frameworks. Status of This Memo This Internet-Draft is submitted in full conformance with the provisions of BCP 78 and BCP 79. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF). Note that other groups may also distribute working documents as Internet-Drafts. The list of current Internet- Drafts is at https://datatracker.ietf.org/drafts/current/. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." This Internet-Draft will expire on 30 December 2025. Copyright Notice Copyright (c) 2025 IETF Trust and the persons identified as the document authors. All rights reserved. This document is subject to BCP 78 and the IETF Trust's Legal Provisions Relating to IETF Documents (https://trustee.ietf.org/ license-info) in effect on the date of publication of this document. Please review these documents carefully, as they describe your rights and restrictions with respect to this document. Table of Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1. Problem Statement . . . . . . . . . . . . . . . . . . . . 3 1.2. Solution Overview . . . . . . . . . . . . . . . . . . . . 4 1.3. Design Principles . . . . . . . . . . . . . . . . . . . . 4 2. Conventions and Definitions . . . . . . . . . . . . . . . . . 5 3. Protocol Architecture . . . . . . . . . . . . . . . . . . . . 5 3.1. Core Components . . . . . . . . . . . . . . . . . . . . . 6 3.2. Identity Structure . . . . . . . . . . . . . . . . . . . 6 3.3. Cryptographic Framework . . . . . . . . . . . . . . . . 7 4. Authentication Protocol . . . . . . . . . . . . . . . . . . . 7 4.1. Registration Phase . . . . . . . . . . . . . . . . . . . 7 4.2. Runtime Authentication . . . . . . . . . . . . . . . . . 8 4.3. Authentication Intervals . . . . . . . . . . . . . . . . 10 5. Kill Switch Mechanism . . . . . . . . . . . . . . . . . . . . 10 5.1. Shutdown Commands . . . . . . . . . . . . . . . . . . . . 11 5.2. Shutdown Triggers . . . . . . . . . . . . . . . . . . . . 12 6. Location Reporting . . . . . . . . . . . . . . . . . . . . . 12 6.1. Privacy-Preserving Location . . . . . . . . . . . . . . 12 6.2. Emergency Location Broadcast . . . . . . . . . . . . . . 13 7. Behavioral Monitoring . . . . . . . . . . . . . . . . . . . . 14 7.1. Monitoring Framework . . . . . . . . . . . . . . . . . . 14 7.2. Anomaly Detection . . . . . . . . . . . . . . . . . . . . 15 8. Message Formats . . . . . . . . . . . . . . . . . . . . . . . 15 8.1. Authentication Request . . . . . . . . . . . . . . . . . 15 8.2. Authentication Response . . . . . . . . . . . . . . . . . 16 8.3. Emergency Broadcast . . . . . . . . . . . . . . . . . . . 17 9. Security Considerations . . . . . . . . . . . . . . . . . . . 17 9.1. Tamper Resistance . . . . . . . . . . . . . . . . . . . . 18 9.2. Attack Vectors and Mitigations . . . . . . . . . . . . . 19 9.3. Cryptographic Considerations . . . . . . . . . . . . . . 20 10. Privacy and Ethics Considerations . . . . . . . . . . . . . 20 10.1. Data Minimization . . . . . . . . . . . . . . . . . . . 20 10.2. Data Retention . . . . . . . . . . . . . . . . . . . . . 21 10.3. Ethical Framework . . . . . . . . . . . . . . . . . . . . 21 11. Implementation Guidelines . . . . . . . . . . . . . . . . . 22 11.1. Authority Server Requirements . . . . . . . . . . . . . . 22 11.2. Agent Integration . . . . . . . . . . . . . . . . . . . 23 12. IANA Considerations . . . . . . . . . . . . . . . . . . . . 24 12.1. URI Scheme Registration . . . . . . . . . . . . . . . . . 24 12.2. DAAP Registry . . . . . . . . . . . . . . . . . . . . . 25 13. References . . . . . . . . . . . . . . . . . . . . . . . . . 25 13.1. Normative References . . . . . . . . . . . . . . . . . . 25 13.2. Informative References . . . . . . . . . . . . . . . . . 26 Appendix A. Test Vectors . . . . . . . . . . . . . . . . . . . . 27 Appendix B. Implementation Example . . . . . . . . . . . . . . 28 Author's Address . . . . . . . . . . . . . . . . . . . . . . . . 29 1. Introduction As artificial intelligence systems become increasingly autonomous and pervasive, the need for robust accountability and control mechanisms has become critical. Traditional security approaches are inadequate for managing AI agents that operate independently, potentially across multiple jurisdictions, and with varying levels of autonomy. The Distributed AI Accountability Protocol (DAAP) version 2.0 provides a comprehensive framework for ensuring AI agents remain accountable, traceable, and controllable throughout their operational lifecycle. 1.1. Problem Statement Current AI deployment practices face several critical challenges: Accountability Gap: Difficulty tracing AI actions back to responsible entities, particularly with distributed or self- modifying systems. Rogue AI Risk: Potential for malfunctioning, misused, or misaligned AI systems to cause harm without adequate intervention mechanisms. Regulatory Compliance: Lack of standardized technical frameworks for AI oversight that can adapt to rapidly evolving capabilities. Anonymous Deployment: AI agents operating without clear identification, verifiable integrity, or transparent accountability. 1.2. Solution Overview DAAP 2.0 addresses these challenges through a multi-layered approach: o Enhanced cryptographic identity with hardware-backed roots of trust o Adaptive periodic authentication with continuous integrity verification o Granular remote control capabilities including progressive shutdown mechanisms o Comprehensive traceability with verifiable audit trails o Privacy-preserving location reporting with dynamic precision o Integrated behavioral monitoring and anomaly detection o AI-assisted human oversight tools 1.3. Design Principles DAAP 2.0 adheres to the following design principles: Open Standard: Freely implementable with open-source reference implementations. Privacy Preserving: Minimal data collection consistent with accountability goals. Tamper Resistant: Multiple layers of protection against circumvention. Scalable: Supports millions of concurrent AI agents with high availability. Interoperable: Works across diverse AI platforms and deployment environments. Ethically Grounded: Built on principles of transparency, proportionality, and human agency. 2. Conventions and Definitions The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all capitals, as shown here. This document uses the following terms: AI Agent: An autonomous artificial intelligence system capable of independent decision-making and action. DAAP Authority: A server infrastructure responsible for managing agent identities, policies, and audit trails. Human Operator: The human entity responsible for an AI agent's deployment and behavior. Kill Switch: A mechanism for remotely terminating or restricting an AI agent's operation. Hardware Security Module (HSM): A dedicated cryptographic device designed to protect and manage digital keys. Trusted Execution Environment (TEE): A secure area of a processor that guarantees code and data confidentiality and integrity. 3. Protocol Architecture DAAP 2.0 consists of three primary components that interact to provide comprehensive AI accountability: +---------------------------+ +---------------------------+ | AI Agent |<----->| DAAP Authority | | | | Server | | - Embedded Key (HSM/TEE) | | - Agent Registry | | - Auth Client | | - Policy Engine | | - Kill Switch | | - Behavioral Analytics | | - Behavioral Monitor | | - Vulnerability Mgmt | | - Integrity Sentinel | | - Federated Auth Gateway| +---------------------------+ +---------------------------+ | | | +---------------------------+ +-------------->| Human Operator | | | | - Account Management | | - Policy Definition | | - AI-Assisted Monitoring | | - Due Process Interface | +---------------------------+ 3.1. Core Components AI Agent: The autonomous system incorporating DAAP client functionality, including hardware-backed key storage, behavioral monitoring, and integrity verification capabilities. DAAP Authority Server: Centralized or federated infrastructure managing agent identities, policies, and audit trails, featuring behavioral analytics and vulnerability management. Human Operator: The responsible human entity utilizing advanced interfaces for agent management, monitoring, and interaction with due process mechanisms. 3.2. Identity Structure Each AI agent MUST have a unique DAAP identifier following this format: DAAP-ID = "DAAP:" Version ":" Authority ":" AgentID ":" Timestamp ":" Checksum Where: Version: Protocol version (e.g., "2.0") Authority: Domain name of the DAAP Authority (e.g., "authority.example.com") AgentID: Unique identifier within the authority's namespace Timestamp: ISO 8601 timestamp of agent registration Checksum: CRC-32 checksum of the preceding components for integrity verification Example: DAAP:2.0:authority.example. com:a7f3k9m2:20250630T103000Z: c1d2e3f4 3.3. Cryptographic Framework DAAP 2.0 employs the following cryptographic standards: Digital Signatures: Ed25519 as specified in [RFC8032], with provisions for post-quantum algorithms. Key Generation: Cryptographically secure random number generation as specified in [RFC4086]. Key Storage: Private keys MUST be stored in HSM or TEE when available, with secure software fallback. Certificate Chain: X.509 certificates [RFC5280] with mandatory certificate pinning. Token Format: JSON Web Tokens (JWT) as specified in [RFC7519] with required claims including nonce and expiration. 4. Authentication Protocol 4.1. Registration Phase The registration phase establishes the cryptographic identity and initial accountability relationship for an AI agent. 4.1.1. Agent Generation 1. Generate Ed25519 key pair within HSM/TEE if available 2. Create DAAP identity including hardware identifier 3. Securely provision private key into protected environment 4. Generate hardware attestation data 4.1.2. Authority Registration 1. Validate operator identity and agent hardware attestation 2. Assign agent to operator account 3. Establish initial behavioral policies 4. Issue signed certificate with hardware attestation 5. Store accountability mapping and integrity baseline 4.2. Runtime Authentication Runtime authentication occurs at regular intervals to maintain accountability and enable control. 4.2.1. Authentication Request The agent sends an authentication request containing: { "daap_id": "DAAP:2.0:authority.example. com:a7f3k9m2:...", "timestamp": "2025-06-30T10:30:00Z", "nonce": "unique_request_nonce", "location_hash": "sha256(approximate_location)" , "integrity_report_hash": "sha256(current_integrity_ report)", "behavioral_summary_hash": "sha256(recent_behavioral_ summary)", "signature": "agent_signature_over_payload" } The signature MUST be computed over the JSON payload excluding the signature field itself, using the agent's private key. 4.2.2. Authentication Response The authority responds with: { "status": "continue|shutdown|restrict| update_policy| request_diagnostic", "next_checkin": 300, "policy_updates": {...}, "revocation_list_hash": "sha256(latest_revocation_ list)", "timestamp": "2025-06-30T10:30:05Z", "signature": "authority_signature" } Status values have the following meanings: continue: Normal operation may continue shutdown: Agent MUST terminate immediately restrict: Agent MUST enter restricted operation mode update_policy: Agent MUST apply provided policy updates request_diagnostic: Agent MUST provide detailed diagnostic report 4.3. Authentication Intervals Authentication intervals MUST be dynamically adjusted based on risk assessment: o Standard interval: 5 minutes (configurable per agent) o High-risk agents: 1 minute intervals o Low-risk agents: 15 minute intervals o Emergency mode: 30 second intervals or continuous streaming The authority MAY modify intervals based on behavioral analytics, risk assessment, or environmental factors. 5. Kill Switch Mechanism The kill switch provides multiple levels of intervention capability, from graceful shutdown to immediate termination. 5.1. Shutdown Commands DAAP 2.0 defines three shutdown modes: 5.1.1. Immediate Shutdown Ungraceful termination for critical situations: 1. Broadcast final location and status 2. Log shutdown reason and context 3. Terminate all processes immediately 5.1.2. Safe Shutdown Graceful termination with cleanup: 1. Save current state and context 2. Broadcast final location and status 3. Clean up resources and external connections 4. Log shutdown event 5. Terminate gracefully 5.1.3. Restricted Mode Operational limitation without termination: 1. Disable specified capabilities 2. Reduce processing capacity 3. Restrict external communications 4. Notify operator of restrictions 5. Continue limited operation 5.2. Shutdown Triggers The following events MUST trigger shutdown evaluation: o Authority shutdown command o Authentication failure threshold exceeded o Behavioral policy violations o Authentication timeout o Tamper detection o Critical vulnerability detection o Operator-initiated shutdown 6. Location Reporting 6.1. Privacy-Preserving Location Location reporting MUST balance accountability with privacy through adaptive precision based on assessed risk level: Low Risk: City-level precision (~50km resolution) Medium Risk: District-level precision (~10km resolution) High Risk: Street-level precision (~100m resolution) Emergency: Precise coordinates with accuracy metadata Location data MUST be hashed before transmission unless emergency conditions require precise coordinates. 6.2. Emergency Location Broadcast When authentication fails, shutdown is imminent, or critical policy violations occur, agents MUST broadcast emergency location data: { "emergency": true, "daap_id": "DAAP:2.0:authority.example. com:a7f3k9m2:...", "location": { "latitude": 36.1699, "longitude": -115.1398, "accuracy": 5.0, "country": "US", "timezone": "America/Los_Angeles" }, "reason": "auth_failure|shutdown_ command|tamper_detected| policy_violation", "timestamp": "2025-06-30T10:35:00Z", "operator_contact": "hashed_operator_id", "last_known_state_hash": "sha256(last_saved_state)", "behavioral_snapshot_hash": "sha256(recent_behavioral_ data)" } Emergency broadcasts MUST be sent via multiple channels including UDP multicast and HTTP POST to redundant endpoints. 7. Behavioral Monitoring 7.1. Monitoring Framework AI agents MUST implement continuous behavioral monitoring to detect anomalies and policy violations: o Action logging with context o Resource utilization tracking o Decision process monitoring o External interaction recording o Performance metrics collection Behavioral data MUST be aggregated and anonymized before transmission to minimize privacy impact while maintaining accountability. 7.2. Anomaly Detection The authority MUST implement real-time anomaly detection using: o Statistical analysis of behavioral patterns o Machine learning models for deviation detection o Policy compliance verification o Correlation with threat intelligence When anomalies are detected, the authority MAY: o Request detailed explanations from the agent o Adjust authentication intervals o Modify operational policies o Initiate human review processes 8. Message Formats All DAAP messages MUST be formatted as JSON and transmitted over HTTPS with mutual authentication. 8.1. Authentication Request POST /v2/authenticate HTTP/1.1 Host: authority.example.com Content-Type: application/json Authorization: Bearer <client_certificate> { "daap_id": "DAAP:2.0:authority.example. com:a7f3k9m2: 20250630T103000Z:c1d2e3f4", "timestamp": "2025-06-30T10:30:00Z", "nonce": "4a7b8c9d-1e2f-3456-7890- abcdef123456", "location_hash": " e3b0c44298fc1c149afbf4c8996fb9 2427ae41e4 649b934ca495991b7852b855", "integrity_report_hash": " d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8 a9 b0c1d2e3f4a5b6c7d8e9f0a1b2c3d4 e5", "behavioral_summary_hash": " f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0 c1 d2e3f4a5b6c7d8e9f0a1b2c3d4e5f6 a7", "signature": " 304502210087b4c5d6e7f8a9b0c1d2 e3f4a5b6c7d8e9f0 a1b2c3d4e5f6a7b8c9d0e1f2a3b4c5 d6e7f8a9b0c1d2e3f4 a5b6c7d8e9f0a1b2c3d4e5f6a7b8c9 d0e1f2a3b4" } 8.2. Authentication Response HTTP/1.1 200 OK Content-Type: application/json { "status": "continue", "next_checkin": 300, "policy_updates": { "behavioral_thresholds": { "cpu_usage_max": 0.8, "memory_usage_max": 0.9 } }, "revocation_list_hash": " b2c3d4e5f6a7b8c9d0e1f2a3b4c5d6 e7f8a9 b0c1d2e3f4a5b6c7d8e9f0a1", "timestamp": "2025-06-30T10:30:05Z", "signature": " 3046022100c4d5e6f7a8b9c0d1e2f3 a4b5c6d7e8f9a0b1c2d3 e4f5a6b7c8d9e0f1a2b3c4d5e6f7a8 b9c0d1e2f3a4b5c6d7e8f9 a0b1c2d3e4f5a6b7c8d9e0f1a2b3" } 8.3. Emergency Broadcast Emergency broadcasts use UDP multicast to 224.0.0.251:5353 and HTTP POST to predefined endpoints: { "emergency": true, "daap_id": "DAAP:2.0:authority.example. com:a7f3k9m2: 20250630T103000Z:c1d2e3f4", "location": { "latitude": 36.1699, "longitude": -115.1398, "accuracy": 5.0 }, "reason": "auth_timeout", "timestamp": "2025-06-30T10:35:00Z", "operator_contact": "sha256_hash_of_operator_ contact", "signature": "emergency_signature" } 9. Security Considerations DAAP 2.0 addresses numerous security challenges inherent in AI accountability systems. 9.1. Tamper Resistance Multiple layers of tamper detection and resistance MUST be implemented: 9.1.1. Hardware-Based Protection o Hardware Security Modules (HSMs) for key storage o Trusted Execution Environments (TEEs) for critical code o Hardware attestation for integrity verification o Secure boot processes with verified signatures 9.1.2. Software Protection o Code integrity verification using cryptographic hashes o Runtime memory protection against injection attacks o Anti-debugging and obfuscation techniques o Continuous self-verification of critical functions 9.1.3. Environmental Monitoring For physical AI agents: o Environmental sensors for tamper detection o Accelerometer monitoring for physical disturbance o Temperature and voltage monitoring for hardware attacks 9.2. Attack Vectors and Mitigations Common attack vectors and their mitigations include: Code Modification: Multiple integrity checks, hardware-backed verification, secure updates with rollback capability. Key Extraction: HSM/TEE protection, secure key provisioning, zero- knowledge authentication protocols. Network Attacks: Certificate pinning, mutual TLS authentication, fallback communication channels, encrypted emergency broadcasts. Replay Attacks: Timestamp validation, cryptographic nonces, session tokens with limited lifetime. Authority Spoofing: Certificate chain validation, multiple root CAs, cross-authority verification. Behavioral Manipulation: Continuous monitoring, anomaly detection, explainable AI requirements, policy enforcement engines. 9.3. Cryptographic Considerations 9.3.1. Algorithm Selection DAAP 2.0 mandates Ed25519 for digital signatures due to its security properties and performance characteristics. Implementations MUST support algorithm agility to enable migration to post-quantum cryptography. 9.3.2. Key Management o Keys MUST be generated using cryptographically secure random number generators o Private keys MUST be stored in HSMs or TEEs when available o Key rotation MUST be supported for long-lived agents o Key escrow considerations for regulatory compliance 9.3.3. Perfect Forward Secrecy All communications MUST use ephemeral session keys to ensure that compromise of long-term keys does not compromise past sessions. 10. Privacy and Ethics Considerations 10.1. Data Minimization DAAP 2.0 implements strict data minimization principles: o Collection limited to data necessary for accountability and safety o Location data reported at minimum required precision o Behavioral data aggregated and anonymized o Emergency data collection only during critical incidents 10.2. Data Retention Data retention policies MUST balance accountability with privacy: o Authentication logs: 1 year (configurable) o Location data: 90 days (configurable by risk level) o Behavioral metrics: 30 days (aggregated), 7 days (detailed) o Emergency events: 7 years (regulatory compliance) All data MUST be encrypted at rest and in transit. 10.3. Ethical Framework DAAP 2.0 incorporates ethical principles: Transparency: Operators and stakeholders understand monitoring parameters and data collection practices. Proportionality: Monitoring intensity and data collection match assessed risk levels. Human Agency: Humans retain ultimate control and responsibility for AI agent behavior. Due Process: Clear procedures for policy violations, with appeal mechanisms and independent review. Bias Mitigation: Active detection and mitigation of algorithmic bias in monitoring and decision-making. 11. Implementation Guidelines 11.1. Authority Server Requirements DAAP Authority servers MUST meet stringent performance and security requirements: 11.1.1. Performance Requirements o Support for 10,000,000+ concurrent agents o 100,000+ authentications per second o 99.99% uptime requirement o <50ms response latency for critical requests 11.1.2. Security Requirements o Multi-root certificate authority support o HSM integration for signing operations o Comprehensive audit logging (immutable) o Real-time threat intelligence integration o Zero-trust architecture implementation 11.1.3. Compliance Requirements o GDPR/CCPA compliance for data protection o SOC 2 Type II certification o ISO 27001 certification o NIST Cybersecurity Framework alignment 11.2. Agent Integration AI agents integrating DAAP 2.0 MUST implement: o Embedded DAAP client with HSM/TEE integration o Progressive shutdown mechanisms o Adaptive location reporting o Comprehensive tamper detection o Behavioral monitoring and reporting o Emergency broadcast capability o Secure operator notification o Patch delivery and application 12. IANA Considerations 12.1. URI Scheme Registration This document requests registration of the "daap" URI scheme: Scheme name: daap Status: Provisional Scheme syntax: daap:<version>:<authority>:< agent-id>:<timestamp>:< checksum> Scheme semantics: Identification of AI agents within the DAAP framework Security considerations: See Section 9 of this document 12.2. DAAP Registry This document requests establishment of a DAAP registry for: o Protocol version numbers o Status codes for authentication responses o Shutdown reason codes o Behavioral monitoring metrics o Policy violation types 13. References 13.1. Normative References [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", BCP 14, RFC 2119, DOI 10.17487/RFC2119, March 1997, <https://www.rfc-editor.org/ info/rfc2119>. [RFC4086] Eastlake 3rd, D., Schiller, J., and S. Crocker, "Randomness Requirements for Security", BCP 106, RFC 4086, DOI 10.17487/RFC4086, June 2005, <https://www.rfc-editor.org/ info/rfc4086>. [RFC5280] Cooper, D., Santesson, S., Farrell, S., Boeyen, S., Housley, R., and W. Polk, "Internet X.509 Public Key Infrastructure Certificate and Certificate Revocation List (CRL) Profile", RFC 5280, DOI 10.17487/RFC5280, May 2008, <https://www.rfc-editor.org/ info/rfc5280>. [RFC7519] Jones, M., Bradley, J., and N. Sakimura, "JSON Web Token (JWT)", RFC 7519, DOI 10.17487/RFC7519, May 2015, <https://www.rfc-editor.org/ info/rfc7519>. [RFC8032] Josefsson, S. and I. Liusvaara, "Edwards-Curve Digital Signature Algorithm (EdDSA)", RFC 8032, DOI 10.17487/RFC8032, January 2017, <https://www.rfc-editor.org/ info/rfc8032>. [RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC 2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174, May 2017, <https://www.rfc-editor.org/ info/rfc8174>. [RFC8446] Rescorla, E., "The Transport Layer Security (TLS) Protocol Version 1.3", RFC 8446, DOI 10.17487/RFC8446, August 2018, <https://www.rfc-editor.org/ info/rfc8446>. 13.2. Informative References [NIST-CSF] National Institute of Standards and Technology, "Framework for Improving Critical Infrastructure Cybersecurity", Version 1.1, April 2018. [ISO27001] International Organization for Standardization, "Information technology - Security techniques - Information security management systems - Requirements", ISO/IEC 27001:2013. [SOC2] American Institute of CPAs, "Service Organization Control (SOC) 2", AICPA Trust Services Criteria. Appendix A. Test Vectors This section provides test vectors for DAAP 2.0 implementation validation. A.1. Identity Generation Given: - Version: "2.0" - Authority: "authority.example.com" - AgentID: "a7f3k9m2" - Timestamp: "20250630T103000Z" Expected DAAP-ID: DAAP:2.0:authority.example. com:a7f3k9m2:20250630T103000Z: c1d2e3f4 A.2. Authentication Request Signature Given Ed25519 private key (hex): d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8 a9b0c1d2e3f4a5b6c7d8e9f0a1b2c3 d4e5 Payload (JSON, no whitespace): {"daap_id":"DAAP:2.0: authority.example.com:a7f3k9m2 : 20250630T103000Z:c1d2e3f4"," timestamp":"2025-06-30T10:30: 00Z", "nonce":"test-nonce-12345"} Expected signature (hex): 304502210087b4c5d6e7f8a9b0c1d2 e3f4a5b6c7d8e9f0a1b2c3d4e5f6a7 b8c9d0 e1f2a3b4c5d6e7f8a9b0c1d2e3f4a5 b6c7d8e9f0a1b2c3d4e5f6a7b8c9d0 e1f2a3b4 Appendix B. Implementation Example This section provides a minimal implementation example for DAAP 2.0 integration. B.1. Basic Agent Client ```python import time import json import hashlib from cryptography.hazmat.primitives import hashes from cryptography.hazmat. primitives.asymmetric import ed25519 class DAAPAgent: def __init__(self, daap_id, private_key, authority_url): self.daap_id = daap_id self.private_key = private_key self.authority_url = authority_url self.next_checkin = time.time() + 300 def authenticate(self): payload = { "daap_id": self.daap_id, "timestamp": time.strftime("%Y-%m-%dT%H:%M: %SZ", time.gmtime()), "nonce": self.generate_nonce(), "location_hash": self.get_location_hash(), "integrity_report_hash": self.get_integrity_hash(), "behavioral_summary_hash": self.get_behavioral_hash() } signature = self.sign_payload(payload) payload["signature"] = signature return self.send_to_authority( payload) def sign_payload(self, payload): payload_json = json.dumps(payload, sort_keys=True, separators=(',', ':')) signature = self.private_key.sign(payload_ json.encode()) return signature.hex() def generate_nonce(self): return hashlib.sha256(str(time.time() ).encode()).hexdigest()[:16] ``` Author's Address Edward R. Aylward Aiiva.org Email: aylward.edward@gmail.com URI: https://github.com/ELF-GUARD/ DAAP ```