Temporal Dynamics and Security Assessment of SRT Protocol: A 96-Day Longitudinal Analysis of Production Streaming Infrastructure

arXiv:2610.26402 · cs.CR, cs.MM · Submitted 2026-10-19 · Read on arXiv

cs.CR, cs.MM

Submitted: 2026-10-19

Updated: 2026-10-19

Comments: 21 pages, 11 figures, published in Journal of Communications (JCM), vol. 21, no. 4, pp. 544-564, 2026

Journal ref: Journal of Communications, vol. 21, no. 4, pp. 544-564, 2026

DOI: 10.12720/jcm.21.4.544-564

License: http://creativecommons.org/licenses/by/4.0/

The gist: 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

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 squared < 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.

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