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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Nong Ye Mingming Xu |
| Copyright Year | 2000 |
| Description | Author affiliation: Dept. of Ind. Eng., Arizona State Univ., Tempe, AZ, USA (Nong Ye; Mingming Xu) |
| Abstract | Intrusion detection is to monitor and capture intrusions into computer and network systems that attempt to compromise the security of computer and network systems. Different intrusion detection techniques exist to evaluate the likelihood of observed activities as a part of an intrusion. When applied to the same observed activities of computer and network systems, different intrusion detection techniques yield different evaluation results. An information fusion technique is required to fuse different results of various intrusion detection techniques for producing a composite value of intrusion likelihood. This paper examines three information fusion techniques based on artificial neural network, linear regression, and logistic regression. These information fusion techniques are compared with respect to their performance. |
| File Size | 368429 |
| File Format | |
| ISBN | 2725700000 |
| DOI | 10.1109/IFIC.2000.859878 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2000-07-10 |
| Access Restriction | Subscribed |
| Rights Holder | Int. Soc. Inf. Fusion |
| Subject Keyword | Intrusion detection Computer networks Decision trees Artificial neural networks Linear regression Logistics Industrial engineering Computerized monitoring Computer security Information security |
| Content Type | Text |
| Resource Type | Article |
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