An Adaptive Secure Data Streaming Architecture for Real-Time Mobile and Cloud-Native Application Systems

Abstract

Real-time mobile and cloud-native applications—such as live dashboards, financial trading, and IoT telemetry—rely on low-latency, high-throughput data streams. Securing these streams under varying client network conditions (e.g., mobile 5G vs. rural 3G) and preserving real-time performance presents a major architectural challenge. Traditional security solutions, which enforce rigid, synchronous checks, often introduce unacceptable latency and fail gracefully under high network jitter. This paper proposes the Adaptive Secure Data Streaming Architecture (ASDA-S), a novel framework that dynamically adjusts the security and data delivery pipeline based on real-time client and network context. ASDA-S leverages a Context-Aware Security Gateway (CASG) that modifies encryption ciphers and stream batch sizes based on client bandwidth and latency constraints. Key to the architecture is a Hierarchical Data Integrity Model (HDIM) that separates critical data fields for high-assurance, low-latency encryption from bulk data, which is compressed and encrypted with a less resource-intensive algorithm. Empirical evaluation, conducted on a simulated real-time financial data feed, demonstrates that ASDA-S achieves a $\mathbf{35\%}$ reduction in end-to-end latency for mobile clients on low-bandwidth networks compared to static, high-assurance encryption baselines, while maintaining $\mathbf{100\%}$ policy compliance for critical data integrity. ASDA-S provides a resilient and highly performant solution for securing continuous data flows in dynamic cloud-to-edge environments.