SBIR Phase I: Red Lambda Neuro-Pattern Classification System

SBIR 第一阶段：Red Lambda 神经模式分类系统

• 批准号: 0610737
• 负责人: Gregory Marchwinski
• 金额: $ 10万
• 依托单位: Red Lambda, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-01 至 2006-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0610737&HistoricalAwards=false
• 关键词: SBIR; Phase; Red; Lambda; Neuro

This Small Business Innovation Research (SBIR) Phase I project investigates large-scale classification problems in enterprise network security. If successful, the project will forward a technology that can detect new protocols and applications in the wild without human intervention. The objectives of the Phase 1 research are: (1) To distill and quantify event classification investigations; (2) To parallelize the findings across an existing proprietary platform; and (3) To test, measure, and compare the results of the integration. The innovation is relevant to the enterprise network security market because security events are characterized by a proliferation of data that is ever-changing. It is difficult for IT professionals and their existing tools to keep pace with the iterations of new security risks. Current solutions tend to over-report or under-report security events leading to inefficiencies in labor allocation in IT departments. The proposed innovation will lead to a network security platform that will draw deeper and richer correlations than is currently available, leading to savings in personnel and a sharper focus on legitimate security events.

这个小型企业创新研究（SBIR）第一阶段项目调查了企业网络安全中的大规模分类问题。如果成功，该项目将提出一种技术，可以在没有人为干预的情况下检测新的协议和应用程序。第一阶段研究的目标是：（1）提取和量化事件分类调查;（2）在现有专有平台上并行处理调查结果;（3）测试、测量和比较集成结果。这项创新与企业网络安全市场相关，因为安全事件的特点是不断变化的数据激增。IT专业人员及其现有工具很难跟上新安全风险的迭代。当前的解决方案往往会高估或低估安全事件，导致IT部门的劳动力分配效率低下。拟议的创新将导致一个网络安全平台，该平台将比目前更深入和更丰富的相关性，从而节省人员并更专注于合法的安全事件。