NeTS:Small: Mapping, Attacking and Defending the BitTorrent Ecosystem

NeTS:Small：绘制、攻击和防御 BitTorrent 生态系统

• 批准号: 0917767
• 负责人: Keith Ross
• 金额: $ 34.99万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0917767&HistoricalAwards=false
• 关键词: NeTS; Small; Mapping; Attacking; Defending

The BitTorrent Ecosystem includes millions of BitTorrent peers, hundreds of active trackers, and dozens of independently-operated torrent discovery sites. The Ecosystem is further fueled with distributed trackers using Distributed Hash Table (DHT) and Peer Exchange (PEX) functionality. The Ecosystem also includes ?interdiction companies," which attempt to curtail the distribution of targeted content.Despite its importance, both in terms of its footprint in the Internet and the influence it has on emerging P2P applications, the BitTorrent Ecosystem is only partially understood today. Many communities (including P2P researchers and developers, ISP researchers and engineers, copyright holders, and law enforcement agencies) would like to have a comprehensive and in-depth understanding of the BitTorrent Ecosystem, as well as tools for mapping the Ecosystem in the future.In this context, the PI and his graduate students are exploring two inter-related research directions. First, they are developing tools and methodologies for comprehensive exploration and mapping of the entire BitTorrent Ecosystem. Second, they are examining of how the Ecosystem can be attacked and defended. The expected results for the mapping research include: new public-domain tools and methodologies for mapping and analyzing the Ecosystem; a comprehensive mapping data set, which will be more than an order of magnitude larger than any existing data set and will essentially cover all trackers and peers in the public Ecosystem; novel estimation methodologies based on importance sampling, incorporating measurement samples from both centralized and distributed trackers.The expected results for the BitTorrent attack/defense research include: measurement and evaluation methodologies of ongoing attacks from ?interdiction companies"; an in-depth study of the seed attack, whereby the attackers attempt to prevent the initial seed from distributing the file into the Ecosystem; machine learning algorithms for defending against the pollution attack in BitTorrent; and tractable deterministic and stochastic models for the dynamics of BitTorrent attacks, providing critical insight into BitTorrent vulnerabilities.

BitTorrent生态系统包括数百万个BitTorrent同行，数百个活跃的跟踪器，以及数十个独立运营的Torrent发现站点。使用分布式哈希表(DHT)和对等交换(PEX)功能的分布式跟踪器进一步推动了生态系统的发展。这个生态系统还包括试图减少目标内容分发的拦截公司。尽管BitTorrent生态系统在互联网足迹和对新兴P2P应用程序的影响方面都很重要，但人们今天对BitTorrent生态系统只有部分了解。许多社区(包括P2P研究人员和开发人员、互联网服务提供商研究人员和工程师、版权所有者和执法机构)希望全面和深入地了解BitTorrent生态系统，以及未来绘制生态系统的工具。在这种背景下，Pi和他的研究生们正在探索两个相互关联的研究方向。首先，他们正在开发工具和方法，以全面探索和绘制整个BitTorrent生态系统。其次，他们正在研究如何攻击和保护生态系统。测绘研究的预期成果包括：用于测绘和分析生态系统的新的公共领域工具和方法；全面的测绘数据集，其将比任何现有数据集大一个数量级，基本上将覆盖公共生态系统中的所有跟踪者和同行；基于重要性抽样的新的估计方法，包括来自集中式和分布式跟踪器的测量样本。BitTorrent攻击/防御研究的预期结果包括：对来自？拦截公司的持续攻击的测量和评估方法；深入研究种子攻击，攻击者试图阻止初始种子将文件分发到生态系统中；用于防御BitTorrent中的污染攻击的机器学习算法；以及用于BitTorrent攻击动态的易处理的确定性和随机模型，提供对BitTorrent漏洞的关键洞察。