ITC-net-audio-5:一个音频流数据集,用于在网络流量分类中的应用程序识别
Mohammad Nikbakht1, Mehdi Teimouri2
1Information Theory and Coding (ITC) Laboratory, University of Tehran, Tehran, Iran.
BMC research notes
|February 27, 2024
概括
研究人员从Skype和WhatsApp等流行的应用程序中创建了一个新的音频流媒体网络流量的数据集. 该资源有助于网络流量分类和应用程序识别.
科学领域:
- 计算机科学 计算机科学
- 网络工程 网络工程
- 数据科学数据科学数据科学
背景情况:
- 应用程序识别对于网络流量分类至关重要.
- 现有的数据集缺乏全面的音频流数据.
- 需要最新的资源来分析音频流应用程序.
研究的目的:
- 为了生成一个新的数据集,专注于音频流媒体网络流量.
- 支持用于音频应用的网络流量分类的进步.
- 为该领域的研究人员和从业人员提供一个有价值的资源.
主要方法:
- 从五个受欢迎的音频流媒体应用程序捕获网络流量:谷歌会面,Skype,电报,WhatsApp和SoundCloud.
- 在语音通话和音乐播放期间使用Wireshark和PCAPdroid收集了500个PCAP文件.
- 采用并发捕获工具,以最大限度地减少背景流量干扰.
主要成果:
- 成功生成了一个音频流媒体网络流量的全面数据集.
- 数据集包括来自趋势应用程序的各种音频流媒体场景.
- 这些数据适用于培训和评估网络流量分类模型.
结论:
- 新的数据集解决了公开可用的音频流媒体流量数据的差距.
- 该资源将提高音频流应用程序识别的准确性和效率.
- 它作为未来网络流量分析和网络安全研究的基础.
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