智能网格入侵检测系统
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An Intelligent Grid Intrusion Detection System
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    摘要:

    结合智能检测技术,并采用先进的分布式体系结构是当前入侵检测研究的一个主要方向.通过对网格与智能检测技术的深入研究,提出了一种智能网格入侵检测系统(intelligent grid intrusion detection system,简称GIDS).该系统部署于网格环境并采用基于神经网络的检测技术;为了实现各数据分析引擎的负载平衡,采用基于资源可用度的调度算法决定任务的分配;为了减少告警数量,采用基于乘性递增线性递减(multiplicative increase linear decrease,简称MILD)的动态窗口调整算法进行警报合成.该入侵检测系统不仅能够充分利用网格上的资源进行入侵行为的发现,而且实现了资源使用的负载均衡,在网络流量大的情况下能够获得较高的检测效率.最后介绍了相应的实验结果分析,表明了该系统的优越性.

    Abstract:

    In grid environment, resource load prediction is one of the most important problems in resource allocation optimization. But load status is difficult to estimate accurately due to the dynamic nature and heterogeneity of grid resource. In response to this issue, a resource allocation strategy that uses sequential game method to predict resource load for time optimization in a proportional resource sharing environment is proposed. The problem of multiple users bidding to compete for a common computational resource is formulated as a multi-player dynamic game. Through finding the Nash equilibrium solution of the multi-player dynamic game, resource load is predicted. Using this load information, a set of user optimal bids is produced to partition resource capacity according to proportional sharing mechanism. The experiments are performed based on the GridSim toolkits and the results show that the proposed strategy could generate reasonable user bids, reduce resource processing time, hence overcome the deficiency of Bredin’s strategy, which is not concerned with resource load variation. The conclusion indicates that employing sequential game method for load prediction is feasible in grid resource allocation and adapts better to the dynamic nature of heterogeneous resource in grid environment.

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魏宇欣,武穆清.智能网格入侵检测系统.软件学报,2006,17(11):2384-2394

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  • 收稿日期:2006-05-14
  • 最后修改日期:2006-08-07
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