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NeTS: Small: Collaborative Research: Protocol Validation using Minimally Supervised Semantic Interpretation of Text

NeTS：小型：协作研究：使用文本的最小监督语义解释进行协议验证

基本信息

批准号：
1814105
负责人：
Dan Goldwasser
金额：
$ 25万
依托单位：
Purdue University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-10-01 至 2021-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1814105&HistoricalAwards=false
关键词：
NeTS Small Collaborative Research Protocol

项目摘要

The networks that comprise the Internet are fundamental to our society, facilitating access to medical and financial services, supporting critical infrastructure such as the power grid, and enabling emergent services such as those provided by autonomous cars and IoT (Internet of Things) devices. Network behavior is dictated by a set of instructions, or protocols, developed and tested over time. Such protocols must operate correctly and comply with requirements that are usually described in a document(s), i.e., in a textual representation. If they do not operate properly, the performance and security of a network could be compromised. The goal of this project is to increase assurance in network protocols, specifically in their compliance to specified rules, in their inter-operability and in their functionality. This project will accomplish this via a novel scheme to perform protocol testing through automated extraction of protocol requirements from their textual specification. This would mark a significant advance in the field, towards automated mechanisms that assure that network protocols are behaving as we expect them to, making networks more reliable and secure. This multidisciplinary project combines expertise from natural language processing and computer networks to create methodologies, frameworks, a knowledge base, and tools for protocol validation for (1) compliance checking, (2) bug finding, and (3) interoperability testing. The general approach is to apply machine learning, semantic parsing and information extraction techniques to structured text (RFCs, internet-drafts) and unstructured text (blogs, forums, and bug reports), and create a knowledge base about the protocols, containing formal information such as message formats, protocol state machine, constraints, and semi-formal information such as temporal properties, tuning conditions and parameters, changes from one version to another, or known bugs. This information is organized into a knowledge base and used to validate protocol implementations through protocol fuzzying, program analysis, software model checking, and measurement methods, to check whether protocols are compliant with their specifications, to detect semantic bugs dependent on intrinsic protocol properties, or check for interoperability issues between different versions, or protocol stacks. This work is guided by protocols from three representative domains -- TCP variants, the SDN ecosystem, and IoT smart home environment.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

构成互联网的网络是我们社会的基础，促进了医疗和金融服务的获取，支持电网等关键基础设施，并实现了自动汽车和物联网（IoT）设备提供的紧急服务。网络行为由一组指令或协议决定，这些指令或协议是随着时间的推移而开发和测试的。这样的协议必须正确地操作并且符合通常在文档中描述的要求，即，在文本表示中。如果它们不能正常运行，网络的性能和安全性可能会受到影响。该项目的目标是提高网络协议的保证，特别是在遵守特定规则、互操作性和功能方面。该项目将通过一种新的方案来实现这一点，该方案通过从文本规范中自动提取协议要求来执行协议测试。这将标志着该领域的一个重大进步，即自动化机制，确保网络协议按照我们的期望运行，使网络更加可靠和安全。这个多学科项目结合了自然语言处理和计算机网络的专业知识，为（1）合规性检查，（2）错误发现和（3）互操作性测试创建方法，框架，知识库和协议验证工具。一般的方法是将机器学习、语义分析和信息抽取技术应用于结构化文本（RFC，互联网草案）和非结构化文本（博客、论坛和错误报告），并创建关于协议的知识库，包含诸如消息格式、协议状态机、约束的正式信息和诸如时间属性、调优条件和参数的半正式信息，从一个版本到另一个版本的更改，或已知的错误。这些信息被组织成一个知识库，并用于通过协议模糊化，程序分析，软件模型检查和测量方法来验证协议实现，以检查协议是否符合其规范，检测依赖于内在协议属性的语义错误，或检查不同版本或协议栈之间的互操作性问题。这项工作由三个代表性领域的协议指导- TCP变体，SDN生态系统和物联网智能家居环境。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估而被认为值得支持。