Dependable Analysis of Network Application Data

一方面，现代互联网流量的多样性和复杂性超出了以前的任何想象。另一方面，所有这些变化都嵌入到Web数据中，不同的应用程序和协议相互嵌套。这意味着区分和隔离不同的行为将非常具有挑战性。实现分析此类网络和应用数据的目标对于任何组织的可靠和安全的网络/服务运营至关重要。在这项研究中，我们特别感兴趣的是建模和理解两个关键的网络和应用程序功能，即超文本传输协议（HTTP）和域名系统（DNS）的变化的影响。HTTP是一种用于分布式、协作式、超媒体信息系统的应用层协议。DNS是一个关键的网络功能，它是一个关键的应用程序，将人类可用的域名映射到机器可用的网络地址（反之亦然）。最近，这两个应用程序都经历了许多变化。它们每天都在发展，其中嵌入了新的协议和服务。因此，当你将它们与互联网初期的早期版本进行比较时，你可以看到它们正在经历一场革命。这可能意味着重大变化将导致网络和域名到IP地址映射服务。这些新版本（变体）将改变连接管理层，以及改变流量和应用程序行为的性质。此外，这通过HTTPS的眼睛将整个互联网连接起来，所有东西似乎都被封装在其中。因此，不同的应用程序和网络行为将变得越来越不透明。这意味着传统的监控和分析方法将不再可能保持网络和服务的健康。网络地址转换和代理服务、流媒体音频/视频和交互式对等应用程序也加入了这一混合，所有这些都增加了分析网络和应用程序数据的挑战。这将挑战我们识别导致不同应用程序和服务的网络故障和网络威胁的行为的能力。因此，拟议的研究计划旨在为智能网络在实践中的成功部署奠定基础和系统。它将通过强大和可靠的基于机器学习的技术来推进网络和应用程序数据分析的最新技术。它将通过解决下一波创新和网络应用数据可靠分析创业的人才缺口来产生HQP。作为回报，这将通过减少网络停机时间和网络支出来运营健康的网络和应用程序，直接使加拿大受益。

On one hand, the variety and complexity of modern Internet traffic exceeds anything previously imagined. On the other hand, all this variety is embedded into web data where different applications and protocols get nested inside one another. This means that differentiating and isolating different behaviours will be very challenging. Realizing the goal of analyzing such network and application data is critical for reliable and secure network / service operations for any organization. In this research, we are specifically interested in modelling and understanding the impact of changes in two critical network and application functionalities, namely Hyper-Text Transfer Protocol (HTTP) and Domain Name System (DNS). HTTP is an application-level protocol for distributed, collaborative, hypermedia information systems. DNS is a critical network functionality in the form of a criticial application that maps human usable domain names to machine usable network addresses (and vice versa). Recently, both of these applications have been going through many changes. They are evolving on a day to day basis with new protocols and services embedded in them. Thus, when you compare them to their earlier versions at the beginning of the Internet, you can see that they are going through a revolution. This potentially implies that significant changes will result in the web and domain name to IP address mapping services. These new versions (variants) will change the connection management layer, as well as changing the nature of the traffic and application behaviours. Furthermore, this threads the entire Internet through the eye of HTTPS into which everything seems to be encapsulated. As a consequence, different application and network behaviours will become more and more opaque. This means that traditional monitoring and analysis approaches for keeping networks and services healthy will no longer be possible. Adding to this mix are network address translation and proxy services, streaming audio / video and interactive peer-to-peer applications, all of which increase the challenges of analyzing the network and application data. This then will challenge our ability to identify behaviours leading to cyber faults and cyber threats for different applications and services. Thus, the proposed research program aims to create the foundations and systems for the successful deployment of intelligent networks in practice. It will advance the state-of-the-art in network and application data analysis via robust and dependable machine learning based techniques. It will produce HQP by addressing the talent gap for the next wave in innovations and entrepreneurship of dependable analysis of network application data. In return, this will directly benefit Canada by reducing network downtime and network expenditures for operating healthy networks and applications.