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Koride, Sudha Gaurinath (2022) Fully Qualified Domain Name(FQDN) as Indexing Parameter for deduplicating the data in Network Devices. Masters thesis, Dublin, National College of Ireland.
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Abstract
The complexity of network devices has increased tremendously due to the demand of accessibility and availability of the network through multiple devices from any location and any time. This has, in turn, increased amount of data that is being generated and stored. One of the factors accounting to it is duplicate or redundant data. These duplicate records can act as security gaps if not handled properly because cyber criminals may use a duplicate record of decommissioned device which is still showing in the Asset Registry as active due to duplication. FQDN is used as indexing parameter to remove the duplicate data from the data obtained through two different network resources: Configuration Management Database(CMDB) & Unknown Device Detection & Response (UDDR). This data is being compared to the data coming from another network resource SolarWinds(SW). This is considered as source-of-truth as it has only unique records in it. Two of the most efficient similarity matching and data deduplicating algorithms AdaBoost and k-Nearest neighbour have been implemented in this research attempt. AdaBoost proved to be a better data deduplication model with an accuracy of 87% while k-Nearest Neighbour model achieved an accuracy of 80%. Ultimately, the efficiency of FQDN to be used as a unique attribute for data deduplication in Network devices was proved.
| Item Type: | Thesis (Masters) |
|---|---|
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > Computer networks Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security |
| Divisions: | School of Computing > Master of Science in Cyber Security |
| Depositing User: | Tamara Malone |
| Date Deposited: | 19 Dec 2022 17:52 |
| Last Modified: | 07 Mar 2023 16:58 |
| URI: | https://norma.ncirl.ie/id/eprint/6017 |
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