Nets: Small: Optimal Design of Anonymous Network Systems under Resource Constraints

网络：小：资源约束下匿名网络系统的优化设计

• 批准号: 1117701
• 负责人: Parvathinathan Venkitasubramaniam
• 金额: $ 30.2万
• 依托单位: Lehigh University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-15 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1117701&HistoricalAwards=false
• 关键词: Nets; Small; Optimal; Design; Anonymous

Privacy in networked systems goes beyond the secrecy of exchanged data; it is equally critical to protect the identities of communicating parties and the paths of data flow. Availability of such networking information is not only a violation of user privacy, but also provides a convenient platform for a malicious adversary to launch more powerful attacks. Anonymous network systems are networks of special routers and proxy servers that provide protection using cryptographic tools and covert relaying. Commonly deployed systems are, however, vulnerable to timing analysis of packet transmissions and do not provide the necessary protection under resource limitations.The principal investigators will investigate the provably optimal design of anonymous network systems under constraints on resources and desired network quality of service (QoS). They will develop a novel quantitative measure of anonymity that takes into account the complete information available to an adversary and the resource and topological constraints of a network. Using the quantitative model, they will explore the following three critical problems in network system design: optimal resource allocation, stochastic routing, and topological design. If successful, the analysis will give rise to novel networking algorithms to achieve anonymity in information exchange that cater to modern paradigms of network design such as mobility and application independence.Broader Impact: The research will have a significant impact in delivering provable privacy for networked systems. The research promotes graduate and undergraduate education in network security and provides access to recent advances in the field to community college students and law enforcement personnel through distance learning programs. In addition, awareness of security vulnerabilities in social networks will be broadened for middle to high school students.

网络系统中的隐私超出了交换数据​​的保密性；保护沟通各方的身份和数据流的路径同样至关重要。此类网络信息的可用性不仅违反了用户隐私，而且还为恶意对手提供了一个方便的平台来发起更强大的攻击。匿名网络系统是特殊路由器和代理服务器的网络，可利用加密工具和秘密继电器提供保护。但是，通常部署的系统容易受到数据包传输的定时分析，并且在资源限制下没有提供必要的保护。 ）。 他们将开发出一种新颖的匿名定量度量，以考虑到对手可用的完整信息以及网络的资源和拓扑约束。使用定量模型，他们将探索网络系统设计中的以下三个关键问题：最佳资源分配，随机路由和拓扑设计。如果成功，该分析将引起新颖的网络算法，以实现信息交换中的匿名性，以符合现代网络设计范式，例如移动性和应用独立性。BroaderImpact：该研究将对为网络系统提供可证明的隐私产生重大影响。该研究促进了网络安全方面的研究生和本科教育，并通过远程学习计划为社区大学生和执法人员提供了对该领域的最新进展的访问。此外，将扩大对中学生的社交网络安全漏洞的认识。