SBIR Phase I: Proactive Network Configuration Analysis

SBIR 第一阶段：主动网络配置分析

• 批准号: 1621685
• 负责人: Ari Fogel
• 金额: $ 22.5万
• 依托单位: Intentionet, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1621685&HistoricalAwards=false
• 关键词: SBIR; Phase; Proactive; Network; Configuration

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project stems from technology that automatically analyzes network configurations for errors. Computer networks are so tightly woven into the fabric of modern business and society that the delivery of almost all products and services relies on them. Yet networks are notoriously difficult to manage correctly today, and configuration errors that compromise availability, security, and performance are common. Today operators are left to simply wait for bad things to happen and then diagnose and repair the errors as quickly as possible to mitigate the damage. The technology developed in this project will enable organizations to identify network security and availability errors before they are introduced into the running network, thereby saving significant time and money, preventing unauthorized access to customer information, and minimizing down time. The project will also lead to a better understanding of the most prevalent kinds of network configuration errors and how to design networks to prevent them.This Small Business Innovation Research (SBIR) Phase I project will perform the research and development necessary to demonstrate the technical feasibility of a proactive approach to detecting network configuration errors, as instantiated in a software tool. The key innovation underlying the approach is the ability to comprehensively and precisely model and validate the behavior of a network solely by analyzing the network's configuration files. The proposed work has three primary technical goals. First, configuration languages are extremely diverse and complex, so the tool currently only supports features that have been used by the networks to which it has been applied. A key challenge is to augment the logical model underlying the tool to support other features that are used by real-world networks. Second, the tool is currently computationally expensive for large networks. Scalability will be improved by leveraging the structure inherent in network configurations and topologies to perform configuration analysis modularly. Third, to be usable by network operators, the tool must integrate with existing source-control repositories and must provide an expressive interface enabling operators to explore the analysis results. In summary, these research directions will turn the software tool from a research prototype into an expressive, scalable, and usable tool for analyzing real networks.

这个小型企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力源于自动分析网络配置错误的技术。计算机网络与现代商业和社会的结构紧密相连，几乎所有产品和服务的交付都依赖于它们。然而，众所周知，当今的网络很难正确管理，而且危及可用性、安全性和性能的配置错误也很常见。今天，运营商只能等待糟糕的事情发生，然后尽快诊断和修复错误，以减轻损害。该项目开发的技术将使组织能够在将网络安全和可用性错误引入运行网络之前识别它们，从而节省大量时间和金钱，防止未经授权访问客户信息，并最大限度地减少停机时间。 该项目还将导致更好地了解最常见的网络配置错误以及如何设计网络以防止它们。这个小型企业创新研究（SBIR）第一阶段项目将进行必要的研究和开发，以证明在软件工具中实例化的主动方法来检测网络配置错误的技术可行性。该方法的关键创新之处在于能够仅通过分析网络的配置文件来全面精确地建模和验证网络的行为。这项工作有三个主要的技术目标。 首先，配置语言是非常多样和复杂的，因此该工具目前只支持已被应用于其的网络所使用的功能。一个关键的挑战是增强工具底层的逻辑模型，以支持真实网络使用的其他功能。 其次，该工具目前对于大型网络来说计算成本很高。可扩展性将通过利用网络配置和拓扑中固有的结构来模块化地执行配置分析来提高。 第三，要让网络运营商使用，该工具必须与现有的源代码控制库集成，并且必须提供一个富有表现力的界面，使运营商能够探索分析结果。 总之，这些研究方向将把软件工具从一个研究原型变成一个有表现力的、可扩展的、可用的工具，用于分析真实的网络。