DISTRIBUTED DATA MINING AND MINING MULTI-AGENT DATA: Basics, Concepts, Methods - Vudasreenivasa Rao
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The problem of distributed data mining is very important in networks. Ina distributed environment , one has distributed probes placed at strategic locations within the network. The problem here is to be able to correlate the data seen at the various probes, and discover patterns in the global data seen at all the different probes. There could be different models of distributed data mining here, but one coul ... Full description
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Description
The problem of distributed data mining is very important in networks. Ina distributed environment , one has distributed probes placed at strategic locations within the network. The problem here is to be able to correlate the data seen at the various probes, and discover patterns in the global data seen at all the different probes. There could be different models of distributed data mining here, but one could involve a NOC that collects data from the distributed sites, and another in which all sites are treated equally. The goal here obviously would be to minimize the amount of data shipped between the various sites ¿ essentially, to reduce the communication overhead. In distributed mining, one problem is how to mine across multiple heterogeneous data sources: multi-database and multi-relational mining. Another important new area is adversary data mining. In a growing number of domains intrusion detection In my project the Intrusion Detection and Reporting system developed to detect unwonted manipulations to computer systems, mainly through the Internet and checking all active services in secure network is described. Packet Detection System is based on signatures method detection.
More Information
| Author | Vudasreenivasa Rao |
|---|---|
| Publisher | LAP LAMBERT Academic Publishing |
| Release year | 2011 |
| Cover type | Softcover |
| EAN | 9783844392739 |