Ambient Security Architecture¶

AICO's ambient security system provides augmented, zero-effort security through continuous, invisible authentication that adapts to risk levels while maintaining natural user interactions. This document outlines innovative security mechanisms that enhance protection without compromising user experience.

Core Principles¶

Zero-Effort Security: Transparent background operation through natural interaction patterns, behavioral analysis, and environmental context
Privacy-First Design: All biometric data, behavioral patterns, and contextual information remain on-device
Adaptive Security Posture: Dynamic adjustment based on real-time risk assessment
Family-Centric Design: Multi-generational usage with age-appropriate safeguards and parental oversight

Core Components¶

Device Identity (Planned)¶

Hardware Fingerprinting: Unique device characteristics
Network Context: IP address patterns and network behavior
Platform Integration: OS-level security features

Behavioral Biometrics (Future Expansion)¶

Typing Patterns: Keystroke dynamics analysis 🚧 Research phase
Interaction Patterns: UI navigation and usage flows 🚧 Research phase
Voice Characteristics: Speaking patterns and vocal fingerprints 🚧 Research phase

Architecture Overview¶

Multi-Layer Ambient Authentication¶

Flow: User Interaction → Ambient Collection → Contextual Analysis → Risk Assessment → Security Response

Collection Layer: Voice patterns, behavioral biometrics, device context, environmental factors Analysis Layer: Trust score calculation, threat detection, anomaly analysis
Response Layer: Transparent access, step-up authentication, protective restrictions, parental notification

Device Binding & Contextual Trust¶

Cryptographic Device Identity¶

Hardware-Backed Device Fingerprinting - Combines multiple hardware identifiers for robust device identity - Uses platform secure enclaves (iOS Secure Enclave, Android StrongBox, Windows TPM) - Creates unique device certificates bound to hardware

Device Identity Generation: Combines hardware identifiers (secure element ID, device model, OS version) to create unique device certificates bound to hardware.

Trust Score Calculation: Verifies cryptographic binding, calculates fingerprint drift, and assesses temporal factors to generate composite trust scores.

Contextual Trust Engine¶

Multi-Factor Analysis: Analyzes location patterns, network context, temporal behavior, and interaction styles against user baselines.

Weighted Scoring: Location (25%), Network (20%), Temporal (25%), Behavioral (30%) factors combine for composite trust score (0.0-1.0).

Risk-Based Authentication (Planned)¶

Low Risk: Seamless access with device trust
Medium Risk: PIN or biometric confirmation
High Risk: Full re-authentication required
Critical Risk: Session lockout and security alerts

Risk-Based Step-Up Authentication¶

Adaptive Authentication Engine¶

Risk Assessment: Evaluates device trust, behavioral anomalies, contextual anomalies, temporal risk, location risk, and network risk using ML-based aggregation.

Authentication Levels: - Transparent (<0.2): PIN + contextual trust verification - Biometric (0.2-0.4): PIN + platform biometric
- Enhanced (0.4-0.7): PIN + biometric + contextual verification - Parental (0.7-0.9): Parental approval required (minors) - Full Re-auth (>0.9): Complete re-authentication required

Progressive Authentication Flow¶

Risk-Based Escalation: Performs initial risk assessment, then escalates through authentication levels based on risk score. Transparent auth verifies contextual trust factors during PIN entry, escalating to biometric verification if trust score is insufficient.

Family-Safe Authentication¶

Parental Oversight: Sends push notifications to linked parent devices for high-risk authentication requests. 5-minute approval timeout with secure context sharing (sensitive data removed).

Social Recovery: Uses Shamir's Secret Sharing (2-of-3 threshold) to distribute encrypted recovery shares across trusted devices. Enables account recovery when minimum threshold of shares is provided.

Hardware Security Integration¶

Platform-Specific Security Features¶

iOS Secure Enclave: Generates hardware-backed keys with biometric protection (TouchID/FaceID). Provides secure signing with fallback to device passcode.

Android StrongBox: Creates hardware-backed keys requiring biometric authentication with 5-minute validity periods. Supports key attestation for device integrity verification.

Cross-Platform Bridge: Unified interface detecting hardware security capabilities (Secure Enclave, StrongBox, TPM, biometrics, attestation) and performing platform-specific attestation.

Privacy-Preserving Analytics¶

Differential Privacy for Behavioral Learning¶

Privacy Budget Management: Uses configurable epsilon values (default 1.0) to control privacy-utility tradeoff. Adds Laplace noise to behavioral aggregates while ensuring non-negative counts.

Pattern Extraction: Identifies significant behavioral patterns from noisy data using significance thresholds, maintaining privacy preservation throughout analysis.

Security Guarantees¶

Threat Mitigation¶

Threat	Mitigation	Implementation
Device Theft	Hardware-backed keys + biometric protection	Secure enclave/StrongBox integration
Credential Replay	Behavioral biometrics + contextual analysis	Continuous authentication
Social Engineering	Multi-factor verification + parental controls	Risk-based step-up authentication
Insider Threats	Least privilege + audit logging	RBAC with comprehensive logging
Privacy Breaches	Local processing + differential privacy	On-device analytics with privacy preservation

Compliance Alignment¶

Zero Trust Architecture: All access verified regardless of source
OWASP Guidelines: Modern authentication and authorization practices
Privacy by Design: Minimal data collection with user control
Family Safety: Age-appropriate security with parental oversight

Integration with AICO Architecture¶

Message Bus Security¶

Topic-level access control based on user identity and risk assessment
Behavioral context propagation through message metadata
Plugin permission boundaries enforced by ambient security

Database Security¶

Risk-based access controls for sensitive data operations
Behavioral audit trails for security monitoring
Family member data isolation with appropriate sharing controls

Frontend Integration¶

Seamless biometric collection during natural interactions
Progressive authentication UI that adapts to risk levels
Family-friendly security indicators and controls

Behavioral Biometric Authentication (Future Expansion)¶

Continuous Behavioral Analysis¶

Touch & Typing Dynamics: Records pressure, duration, velocity, and touch area patterns. Maintains sliding window of events to generate behavioral profiles comparing pressure patterns, typing rhythms, and gesture signatures.

Voice Pattern Recognition: Extracts fundamental frequency, formants, MFCC coefficients, and prosodic features (speech rate, pause patterns). Calculates weighted similarity scores across voice characteristics.

Note: Behavioral biometric authentication represents a future enhancement to the ambient security system. Initial implementation will focus on device binding, contextual trust scoring, and risk-based step-up authentication using existing platform capabilities.