论文标题
DAI：解密并推断实时视频流的质量
DaI: Decrypt and Infer the Quality of Real-Time Video Streaming
论文作者
论文摘要
推断网络服务的质量是网络运营商优化的重要基础。但是，盛行的实时视频流应用程序采用加密来进行安全性，这是提取实时视频的服务质量（QOS）指标的问题。在本文中，我们提出了基于流量的实时视频质量估计器DAI。 DAI可以部分解密加密的实时视频数据，并应用机器学习方法来估计实时视频的关键客观体验质量（QOE）指标。根据实验结果，DAI可以平均准确度为79％，估计客观QOE指标。
Inferring the quality of network services is the vital basis of optimization for network operators. However, prevailing real-time video streaming applications adopt encryption for security, leaving it a problem to extract Quality of Service (QoS) indicators of real-time video. In this paper, we propose DaI, a traffic-based real-time video quality estimator. DaI can partially decrypt the encrypted real-time video data and applies machine learning methods to estimate key objective Quality of Experience (QoE) metrics of real-time video. According to the experimental results, DaI can estimate objective QoE metrics with an average accuracy of 79%.
