Collaborative Research: NetMine: Finding Patterns in Network Data

合作研究：NetMine：寻找网络数据中的模式

• 批准号: 0208950
• 负责人: Michalis Faloutsos
• 金额: $ 12万
• 依托单位: University of California-Riverside
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2006-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0208950&HistoricalAwards=false
• 关键词: Collaborative; Research; NetMine; Finding; Patterns

ABSTRACTWhat is the ``typical" traffic of a link? What constitutes ``abnormal" traffic, and therefore warrants an alert for suspicious behavior (intrusion)?How will the Internet look like next year? These are the questions that the project focuses on.It has two major thrusts:The first is to find patterns in the network traffic, and the second is to find trends in the Internet evolution. The technical merit is in the synergy of the networking and data mining fields, pushing the envelope in both:The networking field will enjoy novel insights and fast tools to predict the network performance. The data mining field will benefit from new problemsand new tools (using fractals, power laws, large-graph algorithms), that will be stress-tested on multiple Gigabytes of real, network data. The broader impact of this work will be a novel insight of the network behavior at the micro and macro level. In addition, the work will explore our ability to predict the network behavior and its evolution. As a result, the work will provide new tools to identify abnormal behavior, that could be due to a security breach like a DDoS attack.

摘要一个链接的“典型”流量是什么？什么构成了“异常”流量，因此需要对可疑行为（入侵）发出警报？明年的互联网会是什么样子？这些都是项目关注的问题。它有两个主要目标：第一个是发现网络流量的模式，第二个是发现互联网发展的趋势。技术优点在于网络和数据挖掘领域的协同作用，推动了两者的发展：网络领域将享受到预测网络性能的新颖见解和快速工具。数据挖掘领域将受益于新问题和新工具（使用分形、幂律、大图算法），这些工具将在千兆字节的真实网络数据上进行压力测试。这项工作的更广泛的影响将是在微观和宏观层面上对网络行为的新见解。此外，这项工作将探索我们预测网络行为及其演变的能力。因此，这项工作将提供新的工具来识别异常行为，这些异常行为可能是由于DDoS攻击等安全漏洞造成的。