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.

这项小型企业创新研究（SBIR）I期项目研究了企业网络安全中的大规模分类问题。如果成功，该项目将转发一项可以在不干预的情况下检测野外新方案和应用的技术。第1阶段研究的目标是：（1）提炼和量化事件分类调查； （2）在现有的专有平台上并行化发现； （3）测试，测量和比较集成结果。该创新与企业网络安全市场有关，因为安全事件的特征是数据的扩散是不断变化的。 IT专业人员及其现有工具很难与新的安全风险的迭代保持同步。当前的解决方案倾向于过度报告或报告安全事件，从而导致IT部门劳动分配效率低下。拟议的创新将导致网络安全平台，该平台将比目前可用的更深，更丰富的相关性，从而节省人员，并更加关注合法安全事件。