CCRI: NEW: CLASSNET: Community Labeling and Sharing of Security and Networking Test datasets

安全和网络测试数据集的社区标记和共享(CLASSNET)项目将向研究社区提供新的、已标记的、丰富和多样化的数据集，以支持网络和安全研究。该项目将为协作、社区驱动的数据丰富和标记开发一个框架，使这些数据集能够用于网络和安全领域的机器学习(ML)。此外，CLASSNET项目将通过多种方法向研究人员提供数据，确保数据的隐私，同时实现灵活的数据计算。该项目还将生成用于研究的各种连续(不断、自动更新)和精选(由人类选择)的数据集。CLASSNET项目将在数据标签、数据分布和数据源方面进行创新。在数据标签方面，CLASSNET协作框架将为研究人员之间共享注释提供一个低摩擦的框架。该框架将通过反馈机制和用户信用来激励标记，并支持批量、自动、算法标记。在数据分发方面，CLASSNET将支持多种数据访问方式，从下载匿名数据到在云中、在提供商机器上或通过代码到数据的方法处理数据。最后，CLASSNET数据源将提供对网络和安全研究有用的新的、多样化的、连续的和经过管理的数据集，包括流量包和流量、网络望远镜数据、域名系统(DNS)数据和互联网拓扑数据。该项目的直接影响将包括支持新的安全、网络和ML研究和教育的新型标记、经过管理和连续的数据集，影响到一个大的社区。这些数据的更广泛影响将是促进研究和教育，这将使互联网更安全、更稳定、更安全，并将增加社区对互联网的了解。鉴于互联网对远程工作、远程医疗、远程学习、电子商务和电子政务的重要性，这些改进将产生广泛的社会影响。此外，CLASSNET数据集将支持研究生和本科教育以及新的博士研究的数据驱动练习。CLASSNET项目在多种数据获取途径上的创新，与自动化和激励的丰富框架相结合，将提高信息技术相关学科负责任的数据共享的最新水平。该项目的网站将是https://ant.isi.edu/classnet/.该网站将在项目完成后继续运营。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The Community Labeling and Sharing of Security and Networking Test datasets (CLASSNET) project will provide new, labeled, rich and diverse datasets to the research community to support network and security research. The project will develop a framework for collaborative, community-driven enrichment and labeling of data, enabling use of these datasets for machine learning (ML) in networking and security. Furthermore, the CLASSNET project will make data available to researchers through multiple methods, ensuring privacy of data while enabling flexible data computation. The project will also generate diverse continuous (constantly, automatically updated) and curated (selected by human) datasets for research use.CLASSNET project will innovate in dimensions of data labeling, data distribution and data sources. In data labeling, the CLASSNET collaborative framework will provide a low-friction framework for sharing annotations among researchers. The framework will incentivize labeling with feedback mechanisms and user credits, and support bulk, automatic, algorithmic labeling. In data distribution, CLASSNET will support multiple ways of data access, ranging from downloading anonymized data to processing data in the cloud, on provider machines or via the code-to-data approach. Finally, CLASSNET data sources will provide new, diverse, continuous, and curated datasets that are useful for network and security research, including traffic packets and flows, network telescope data, Domain Name System (DNS) data and Internet topology data.The immediate impact of this project will include new types of labeled, curated and continuous datasets that enable new security, networking, and ML research and education, impacting a large community. The broader impact of this data will be to foster research and education, which will make the Internet safer, more stable, and more secure, and will increase the community's knowledge about the Internet. With the Internet's importance for tele-work, tele-medicine, remote learning, e-commerce and e-government, these improvements will have a broad societal impact. In addition, CLASSNET datasets will support data-driven exercises for graduate and undergraduate education, and new PhD research. CLASSNET project's innovations in multiple pathways to data access, combined with The automated and incentivized enrichment framework, will improve the state-of-the-art for responsible data sharing in related disciplines of information technology.The project website will be https://ant.isi.edu/classnet/. The website will remain operational after the project completes.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.