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之前的想象。另一方面，所有这些变化都嵌入到网络数据中，不同的应用程序和协议相互嵌套在一起。这意味着区分和隔离不同的行为将是非常具有挑战性的。实现分析此类网络和应用程序数据的目标对于任何组织的可靠、安全的网络/服务运营都至关重要。在这项研究中，我们特别感兴趣的是建模和了解两个关键网络和应用程序功能的变化的影响，即超文本传输协议(HTTP)和域名系统(DNS)。HTTP是一种用于分布式、协作性、超媒体信息系统的应用层协议。DNS是一种关键网络功能，其形式为关键应用程序，它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，并嵌入了新的协议和服务。因此，当你把它们与互联网诞生之初的早期版本进行比较时，你会发现它们正在经历一场革命。这可能意味着重大变化将导致Web和域名到IP地址的映射服务。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，这使得整个互联网穿过HTTPS的眼睛，似乎一切都被封装在其中。因此，不同的应用和网络行为将变得越来越不透明。这意味着，保持网络和服务健康的传统监测和分析方法将不再可能。此外，还有网络地址转换和代理服务、流音频/视频和交互式点对点应用，所有这些都增加了分析网络和应用数据的挑战。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创建基础和系统。它将通过稳健和可靠的基于机器学习的技术，推动网络和应用数据分析的最先进水平。它将通过解决下一波网络应用数据可靠分析的创新和创业浪潮中的人才缺口来产生HQP。作为回报，这将减少网络停机时间和运营健康网络和应用程序的网络支出，从而直接使加拿大受益。

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.