Back
INTERMEDIATE // MULTI LAYER STACKING

MULTI LAYER STACKING

Combine ABIS with other intelligence layers for comprehensive security

8 Modules
6 Hours
Intermediate Level
01
Architecture

Layer Composition

ABIS is one intelligence layer among many. Learn to compose multiple layers—fraud detection, identity verification, device fingerprinting—into unified security architecture.

Topics Covered
  • Layer types and capabilities
  • Composition patterns
  • Data flow between layers
  • Conflict resolution
  • Unified scoring
45 min
Start →
02
Flow Control

Orchestration Patterns

Coordinate multiple intelligence layers efficiently. Sequential, parallel, and conditional orchestration patterns for different use cases.

Topics Covered
  • Sequential orchestration
  • Parallel execution
  • Conditional branching
  • Early termination
  • Result aggregation
50 min
Start →
03
Layer Integration

Device Intelligence

Integrate device fingerprinting with ABIS behavioral analysis. Correlate device signals with behavioral patterns for comprehensive risk assessment.

Topics Covered
  • Device fingerprint integration
  • Browser/app attribution
  • Device reputation scoring
  • Cross-device linking
  • Emulator detection
55 min
Start →
04
Layer Integration

Identity Verification

Combine ABIS with identity verification services. Layer behavioral signals on top of KYC/KYB checks for enhanced fraud prevention.

Topics Covered
  • KYC integration patterns
  • Document verification
  • Biometric correlation
  • Identity graph analysis
  • Synthetic identity detection
50 min
Start →
05
Layer Integration

Threat Intelligence

Enrich ABIS assessments with external threat intelligence. IP reputation, known bad actors, and threat feed integration.

Topics Covered
  • IP reputation services
  • Threat feed integration
  • Known actor databases
  • Dark web monitoring
  • Real-time blocklists
45 min
Start →
06
Aggregation

Score Fusion

Combine scores from multiple layers into unified risk assessments. Weighted averaging, ensemble methods, and ML-based fusion.

Topics Covered
  • Weighted score combination
  • Ensemble methods
  • ML-based fusion
  • Confidence propagation
  • Score calibration
55 min
Start →
07
Performance

Latency Management

Multi-layer stacks add latency. Optimize performance through parallelization, caching, and intelligent layer selection.

Topics Covered
  • Parallel execution
  • Result caching
  • Adaptive layer selection
  • Timeout strategies
  • Latency budgeting
45 min
Start →
08
Observability

Stack Monitoring

Monitor multi-layer stack health and performance. Track individual layer metrics and end-to-end stack behavior.

Topics Covered
  • Layer health metrics
  • Stack performance dashboards
  • Anomaly detection
  • Alert configuration
  • Capacity planning
40 min
Start →