发明申请
- 专利标题: NETWORK INTRUSION DATA ITEM CLUSTERING AND ANALYSIS
- 专利标题(中): 网络入侵数据项集合与分析
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申请号: US14487021申请日: 2014-09-15
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公开(公告)号: US20160366164A1公开(公告)日: 2016-12-15
- 发明人: David Cohen , Jason Ma , Bing Jie Fu , Ilya Nepomnyashchiy , Steven Berler , Alex Smaliy , Jack Grossman , James Thompson , Julia Boortz , Matthew Sprague , Parvathy Menon , Michael Kross , Michael Harris , Adam Borochoff
- 申请人: Palantir Technologies Inc.
- 主分类号: H04L29/06
- IPC分类号: H04L29/06
摘要:
Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyses (also referred to herein as “summaries” or “conclusions”) of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures.
公开/授权文献
- US09998485B2 Network intrusion data item clustering and analysis 公开/授权日:2018-06-12
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