Dinâmica Temporal e Avaliação de Segurança do Protocolo SRT: Uma análise longitudinal de 96 dias da infraestrutura de transmissão de produção / Temporal Dynamics and Security Assessment of SRT Protocol: A 96-Day Longitudinal Analysis of Production Streaming Infrastructure (2026) (Portuguese)

Este estudo guia uma análise longitudinal de 96 dias do comportamento do protocolo de transporte confiável seguro (SRT) em um ambiente de transmissão de produção entre o Iraque e a Turquia, examinando 262,672 amostras métricas de data de transporte e 5,033,104 medições de assinatura de recursos do sistema coletadas entre outubro de 2025 e janeiro de 2026. A pesquisa aborda padrões de tempo, relações de recursos do sistema, vulnerabilidade de ataque e detecção de anomalias. Os resultados revelam variação temporal significativa: o reconhecimento negativo exibe variação horária de 7,6 vezes e variação diária de 11,05 vezes (p < 0,001), embora com tamanhos de efeito pequenos (eta^2 < 0,04), indicando que o período de tempo explica menos de 4 por cento do estudo de variância de segurança total. A utiliza

Abstract

This study presents a 96-day longitudinal analysis of Secure Reliable Transport (SRT) protocol behavior in a production streaming environment between Iraq and Turkey, examining 262,672 transport metric samples and 5,033,104 system resource measurements collected between October 2025 and January 2026. The research addresses temporal patterns, system-resource relationships, attack vulnerability, and anomaly detection. Results reveal significant temporal variation: Negative Acknowledgment exhibits 7.6-fold hourly variation and 11.5-fold daily variation (p < 0.001), though with small effect sizes (eta^2 < 0.04), indicating that temporal period explains less than 4 percent of total variance. Central Processing Unit (CPU) utilization emerges as the strongest system-level correlate of transport variation (r = 0.617 with NAK rate). Controlled User Datagram Protocol (UDP) flood experiments at 500 packets per second cause CPU increases of 176 to 806 percent, while SRT transport metrics change by only plus or minus 13 percent demonstrating protocol resilience through the Automatic Repeat Request mechanism. An unexpected anomaly reaching 97.7 percent CPU enabled signature-based differentiation between attack types. A Z-score anomaly detection method outperforms fixed thresholds, detecting all 7 security events. This study contributes the longest temporal characterization of SRT metrics reported to date, the first system-SRT correlation analysis, and the first controlled security assessment of SRT infrastructure. These findings provide actionable guidance for capacity planning, security hardening, and multi-metric monitoring of production SRT deployments.

Topics: Computer science, Dynamics (music), Production (economics), Real-time computing, System dynamics, Computer network

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