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A three-tier IDS via data mining approach

机译:通过数据挖掘方法进行三层ID

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Welcome to the Third ACM Workshop on Mining Network Data.. >Today's IP networks are extensively instrumented for collecting a wealth of information including traffic traces (e.g., packet or flow level traces), control information (e.g., on router forwarding tables, BGP and OSPF updates), and management data (e.g., alarms, SNMP traps). The real challenge is to process and analyze this vast amount of primarily unstructured information and extract structures, relationships, and "higher level knowledge" embedded in it and use it to aid network management and operations. The goal of this workshop is to explore new directions in network data collection, storage, and analysis techniques, and their application to network monitoring, management, and remediation. The workshop provides a venue for researchers and practitioners from different backgrounds, including networking, data mining, machine learning, and statistics, to get together and collaboratively approach this problem from their respective vantage points. >18 papers were submitted to the workshop and underwent a rigorous single blind review and discussions by the PC members. Finally papers were selected after detailed discussions at the PC meeting. Given the one-day format for the workshop, the Program Committee was only able to accept 9 papers.
机译:欢迎来到挖掘网络数据的第三个ACM研讨会。 >今天的IP网络是广泛的仪器,用于收集包括流量迹线(例如,数据包或流级迹线)的大量信息,控制信息(例如,在路由器转发表,BGP和OSPF更新)以及管理数据(例如,警报,SNMP陷阱)。真正的挑战是处理和分析这种大量非结构化信息和提取结构,关系和“更高级别的知识”,并使用它来帮助网络管理和操作。该研讨会的目标是探索网络数据收集,存储和分析技术的新方向,以及它们在网络监控,管理和修复中的应用。该研讨会为来自不同背景的研究人员和从业者提供了一个场所,包括网络,数据挖掘,机器学习和统计数据,统计,从各自的有利点中聚集在一起并协作地接近这个问题。 > 18篇论文已提交向讲习班和PC成员进行严格的单一盲目审查和讨论。最后在PC会议上详细讨论后选择了论文。鉴于研讨会的一天格式,计划委员会只能接受9篇论文。

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