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Titlebook: Applications of Data Mining in Computer Security; Daniel Barbará,Sushil Jajodia Book 2002 Springer Science+Business Media New York 2002 In

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11#
發(fā)表于 2025-3-23 12:02:32 | 只看該作者
https://doi.org/10.1007/978-3-319-13183-2tion. This chapter surveys a representative cross section of these research efforts. Moreover, four characteristics of contemporary research are identified and discussed in a critical manner. Conclusions are drawn and directions for future research are suggested.
12#
發(fā)表于 2025-3-23 17:43:19 | 只看該作者
13#
發(fā)表于 2025-3-23 20:52:47 | 只看該作者
Data Mining for Intrusion Detection,tion. This chapter surveys a representative cross section of these research efforts. Moreover, four characteristics of contemporary research are identified and discussed in a critical manner. Conclusions are drawn and directions for future research are suggested.
14#
發(fā)表于 2025-3-24 01:51:07 | 只看該作者
15#
發(fā)表于 2025-3-24 05:21:21 | 只看該作者
16#
發(fā)表于 2025-3-24 08:15:38 | 只看該作者
https://doi.org/10.1007/978-3-031-27990-4s. We present three algorithms for detecting which points lie in sparse regions of the feature space. We evaluate our methods by performing experiments over network records from the KDD CUP 1999 data set and system call traces from the 1999 Lincoln Labs DARPA evaluation.
17#
發(fā)表于 2025-3-24 11:37:04 | 只看該作者
Why Don’t Scientists Respect Philosophers?em with general classes of components that can be easily changed within the framework of the system. We also present specific examples of system components including auditing sub-systems, model generators for misuse detection and anomaly detection, and support for visualization and correlation of multiple audit sources.
18#
發(fā)表于 2025-3-24 17:52:44 | 只看該作者
A Geometric Framework for Unsupervised Anomaly Detection,s. We present three algorithms for detecting which points lie in sparse regions of the feature space. We evaluate our methods by performing experiments over network records from the KDD CUP 1999 data set and system call traces from the 1999 Lincoln Labs DARPA evaluation.
19#
發(fā)表于 2025-3-24 20:48:08 | 只看該作者
Adaptive Model Generation,em with general classes of components that can be easily changed within the framework of the system. We also present specific examples of system components including auditing sub-systems, model generators for misuse detection and anomaly detection, and support for visualization and correlation of multiple audit sources.
20#
發(fā)表于 2025-3-25 02:16:16 | 只看該作者
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