Cyber-Defense Technical Architecture Blueprint

0. Design Goals and Threat Model

0.1 Design Goals

Detect AI-enabled impersonation (text/voice/video), synthetic identities, and coordinated manipulation.
Prevent account takeover, executive impersonation, payment diversion, and social engineering escalation.
Respond with automated containment + human-in-the-loop (HITL) escalation.
Prove authenticity (content provenance, identity attestation) with auditable evidence.
Scale across platforms, channels, and jurisdictions without brittle single-point controls.

0.2 Adversary Model (Practical)

Hybrid operator model: LLM automation + human closers
Capabilities: deepfake voice/video, synthetic profile farms, malware-free social engineering, credential stuffing, SIM swap, payment diversion, “CEO fraud”, vendor compromise, doc forgery, crypto laundering
Constraints: needs onboarding surfaces, account access, payment rails, and sustained engagement loops

1. System Overview (Layered Defense)

RIAS is a layered architecture with 6 planes:

Identity & Trust Plane (who is speaking/acting)
Channel Security Plane (email/chat/voice/video)
Content Authenticity Plane (provenance + deepfake signals)
Behavior & Fraud Intelligence Plane (patterns, graphs, risk scoring)
Orchestration & Response Plane (SOAR, policy, containment)
Governance & Evidence Plane (audit, compliance, chain-of-custody)

2. Identity & Trust Plane

2.1 Core Components

Decentralized/portable identity (optional): W3C Verifiable Credentials (VCs) for humans, vendors, executives
Enterprise identity: IdP (SAML/OIDC), phishing-resistant MFA (FIDO2/WebAuthn), device posture (MDM/EDR attestation)
Privilege control: PAM for admin actions; JIT access; session recording
High-risk persona hardening: executives, finance, HR, IT admins

2.2 Strong Authentication Pattern (Anti-Impersonation)

FIDO2 + device binding for all privileged users
Step-up auth on: payment approvals, vendor bank changes, wire transfers, password resets
Out-of-band verification with cryptographic challenge (not SMS):
- Secure app push with signed challenge
- Hardware security key challenge
- “Known channel” callback registry for high-value approvals

2.3 Identity Assurance Levels (IAL)

Define IAL tiers and enforce per action:

IAL0 anonymous / public
IAL1 basic verified (email/phone)
IAL2 strong verified (KYC-lite + device binding)
IAL3 high assurance (in-person / notarized / org attestation + FIDO2 + hardware-bound keys)

Use policy: risk score + action criticality → required IAL.

3. Channel Security Plane (Email, Chat, Voice, Video)

3.1 Email

DMARC/DKIM/SPF enforced + inbound quarantine
Brand protection: BIMI + monitored lookalike domains
Secure email gateways with:
- URL detonation
- attachment sandboxing
- conversation hijack detection

3.2 Messaging & Collaboration (WhatsApp/Signal/Teams/Slack)

Enterprise secure messaging for critical workflows; disallow approvals in consumer apps
Signed approvals: approvals only valid if issued from a controlled app with cryptographic signing
DLP + anomaly monitoring for external invites, file shares, mass DMs

3.3 Voice & Video

Require “verified sessions” for sensitive calls:
- Meeting join requires org identity (OIDC)
- Real-time liveness challenge (random phrase + head motion + time-bound token)
Callbacks: for finance/vendor changes, callback to pre-registered numbers only

4. Content Authenticity Plane (Provenance + Deepfake Detection)

4.1 Provenance (Preferred)

C2PA content credentials for internal media generation and executive communications
Watermarking/signatures for internal video statements
Document signing (PKI) for contracts, invoices, bank-change forms

4.2 Detection (Necessary)

Deploy multi-modal detectors as signals, not single-truth:

Image: diffusion/GAN artifact classifiers, metadata inconsistencies
Audio: voice-clone spectral features, phase artifacts, neural vocoder fingerprints
Video: lip-sync drift, eye-blink/physiological cues, frame-level generation traces
Text: stylometry + conversational entropy metrics + prompt-injection patterns

Key principle: provenance beats detection. Detection is probabilistic; provenance is enforceable.

5. Behavior & Fraud Intelligence Plane

5.1 Telemetry Inputs

Identity logs: IdP, MFA, PAM
Endpoint: EDR, device posture
Network: DNS/HTTP proxy, firewall, VPN
Channels: email/chat call metadata (not necessarily content)
Financial workflows: invoice changes, wire templates, vendor master edits
OSINT: lookalike domains, social profile farms, breached credential monitoring

5.2 Core Analytics

A) Risk Scoring Engine (Real-time)

Entity: user, device, session, vendor, conversation thread
Features:
- geo-velocity anomalies
- impossible travel
- login novelty
- conversation cadence anomalies (bot-like timing)
- financial request patterns
- vendor change anomalies
- domain reputation + newly registered domains

B) Graph Intelligence (Campaign Detection)

Build a graph of:
- accounts ↔ devices ↔ IPs ↔ domains ↔ payment destinations ↔ message threads
Detect:
- profile farms
- coordinated targeting waves
- repeated “script” patterns across victims
- mule account routing clusters

C) Deception Pattern Library

Maintain a continuously updated library:

Romance scam escalation patterns
CEO fraud scripts
vendor bank-change playbooks
“urgent invoice” language templates
“no video due to security policy” avoidance motifs

6. Orchestration & Response Plane (SOAR)

6.1 Response Modes

Soft controls (friction): step-up auth, warnings, forced callbacks
Hard controls (containment): block transfer, suspend account, isolate endpoint, quarantine email thread
HITL escalation: security analyst + finance controller review

6.2 Automated Playbooks (Examples)

Vendor Bank Change Request
- If request arrives via email/chat: freeze change
- Trigger callback to registry + require signed doc + step-up auth
- If mismatch: flag vendor entity + create incident
Executive Impersonation Attempt
- Detect: sender lookalike + urgency language + payment keyword
- Auto-quarantine + notify exec assistant + require verified channel confirmation
Deepfake Video Call Suspected
- If detector signals exceed threshold + identity assurance low:
  - enforce live challenge
  - if fail: terminate session, preserve evidence, escalate

7. Governance & Evidence Plane

7.1 Evidence Handling (Chain of Custody)

Store raw artifacts with hashes:
- email headers
- chat export metadata
- call metadata + recording (if legal)
- files received
- detector outputs + model version
Maintain immutable audit log (WORM storage)