Federated Stream-Processing and Latency-Gated Response for Cross-Sector Threat Detection and Collaborative Containment
Namit Mohale

TL;DR
This paper introduces a federated stream-processing framework for rapid cross-sector threat detection and containment, capable of handling high-throughput data with minimal delay.
Contribution
It presents a novel, high-throughput, latency-gated threat detection system with a stateless dispatcher, in-memory workers, and a deterministic reconciliation method, advancing real-time cybersecurity defenses.
Findings
Achieves under 7 seconds processing overhead.
Converges detection and response within 12-20 seconds.
Handles 500,000 events per second workload effectively.
Abstract
Critical infrastructure defense is fundamentally bottlenecked by the operational reality that preventive controls are frequently bypassed by sophisticated supply-chain compromises and stolen administrative credentials. When prevention fails, defense relies entirely on rapid, post-ingress threat detection and automated response across sovereign sectors. We present a novel, federated, high-throughput stream-processing and correlation framework designed to detect coordinated cross-sector threat campaigns and orchestrate containment at machine speed. By utilizing a stateless Pre-Filtering Dispatcher Subsystem (PFDS), in-memory lock-sharded state workers, and a 95% statistical watermark heuristic, our system maintains detection momentum during network partitions to evacuate speculative alerts. Delayed telemetry is subsequently reconciled directly within a version-keyed columnar storage…
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