EAGER: Deep Network Analysis

EAGER：深度网络分析

• 批准号: 1251029
• 负责人: Prasant Mohapatra
• 金额: $ 15万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1251029&HistoricalAwards=false
• 关键词: EAGER; Deep; Network; Analysis

Deep packet inspection (DPI) is an established methodology used by ISPs for performance enhancements, security protections, behavioral advertising, and content filtering. However, the limitations of DPI and its applications are becoming more and more evident with the increase in network traffic and the variations in usage patterns. In this exploratory project, the PI will introduce the notion of Deep ``Network" Inspection (DNI) that will go beyond DPI in exploring correlations among multiple networks and other aggregated parameters from multi-genre networks and behaviors. DNI will use broader knowledge including social network relevancies, information network, modalities of accesses, device characteristics, past and present user profiles at various levels of aggregations; thus going far beyond the realm of isolated characterizations of communication networks. Primary goals of DNI include the reduction in the ?search space? for real-time analysis and the complexity of pattern discoveries, and the discovery of relationships which may not be detectable by single-network inspection (such as DPI). The goal of this project is to do an initial study to motivate and explore the capabilities of DNI, the challenges therein, scope of inspections, and potential applications. The outcome of this exploratory study would potentially open up an enriched area for further research in the domains of network science. In terms of broader impact, the proposed project will also instigate researchers in both academics as well as industry to explore this new domain on network inspection, which may have significant potential in a variety of applications, and education of students.

深度数据包检测（DPI）是ISP用于性能增强、安全保护、行为广告和内容过滤的一种既定方法。然而，随着网络流量的增加和使用模式的变化，DPI及其应用的局限性变得越来越明显。在这个探索性项目中，PI将引入深度“网络”检测（DNI）的概念，该概念将超越DPI，探索多个网络之间的相关性以及来自多类型网络和行为的其他聚合参数。DNI将使用更广泛的知识，包括社交网络相关性，信息网络，访问方式，设备特性，过去和现在的用户配置文件在不同层次的聚合;从而远远超出了通信网络的孤立表征的领域。DNI的主要目标包括减少？搜索空间？用于实时分析和模式发现的复杂性，以及发现可能无法通过单网络检查（如DPI）检测到的关系。该项目的目标是做一个初步的研究，以激励和探索DNI的能力，其中的挑战，检查范围和潜在的应用。这项探索性研究的结果可能会为网络科学领域的进一步研究开辟一个丰富的领域。就更广泛的影响而言，拟议的项目还将鼓励学术界和工业界的研究人员探索网络检测这一新领域，这可能在各种应用和学生教育方面具有巨大潜力。