System Architecture

The proposed continuous authentication system is designed as a modular, multimodal architecture that continuously evaluates user identity during an active session. The architecture prioritizes scalability, low latency, and seamless integration with existing enterprise identity and access management platforms.

At a high level, the system consists of four primary layers: signal acquisition, feature extraction, multimodal fusion, and decision and integration. Each layer is independently extensible, enabling the system to adapt to new data sources, models, and deployment constraints.

Signal Acquisition Layer

The signal acquisition layer is responsible for collecting behavioral and contextual signals during an active user session. These signals may include keystroke dynamics, mouse movement patterns, interaction timing, and contextual attributes derived from the execution environment. Data collection is designed to be passive and non-intrusive, ensuring minimal impact on user experience.

Feature Extraction Layer

Raw signals collected from individual modalities are processed through modality-specific feature extraction pipelines. Deep learning models are used to learn discriminative representations that capture user-specific behavioral patterns while remaining resilient to short-term variability and noise.

Multimodal Fusion Layer

The multimodal fusion layer combines features from multiple modalities to generate a unified representation of user behavior. Fusion is performed using deep learning–based techniques that enable the system to learn cross-modal relationships and compensate for weaknesses in individual signals. This approach improves robustness compared to single-modality authentication mechanisms.

Decision and Integration Layer

The decision layer produces a continuous authentication confidence score that reflects the likelihood that the current user matches the authenticated identity. This score can be evaluated against adaptive thresholds to trigger actions such as session continuation, step-up authentication, or access restriction.

The system is designed to integrate with enterprise IAM platforms by exposing authentication outcomes through standard interfaces. This allows continuous authentication to complement existing access control and policy enforcement mechanisms without replacing them.