@article{4847,
  author = {H. Ketmaneechairat, P. Oothongsap, A. Mingkhwan},
  title = {Classical Network Metrics Fail to Predict Continuous Transmission Reliability in Federated Secure Environments},
  journal = {Journal of Networking Technology},
  year = {2026},
  volume = {17},
  number = {4},
  doi = {https://doi.org/10.6025/jnt/2026/17/4/222-239},
  url = {https://www.dline.info/jnt/fulltext/v17n4/jntv17n4_3.pdf},
  abstract = {The increasing deployment of federated learning, edge computing, and Internet of Things (IoT) infrastructures
necessitates robust frameworks for evaluating data transmission reliability in secure environments.
Traditionally, communication quality is assessed using classical network performance metrics such as
bandwidth, latency, packet loss, encryption time, and distributed node count. However, it remains unclear
whether these conventional indicators adequately capture continuous transmission reliability under complex
security, privacy, and trust constraints. This study investigates the predictive utility of five classical network
metrics across two distinct outcomes: continuous transmission reliability and categorical transmission
status. Using a Network Transmission Dataset comprising 13,000 records, we applied correlation analysis,
linear and non-linear regression (Ordinary Least Squares, Random Forest, Gradient Boosting), and
classification models (Multinomial Logistic Regression, Random Forest). The results reveal a striking
dissociation: classical metrics exhibit near zero correlation with continuous reliability (R2  , failing to
explain its variance. Conversely, the same metrics achieve approximately 72% accuracy in classifying
categorical transmission status, driven predominantly by packet loss (54.6%) and network latency (30.9%).
These findings demonstrate that classical network metrics are fundamentally insufficient for predicting
continuous transmission reliability in federated secure environments. Comprehensive reliability assessment
frameworks must therefore incorporate multidimensional security, privacy, and trust variables rather than
relying exclusively on traditional Quality of Service (QoS) indicators.},
}