Analysis of Cyber-Intelligence Frameworks for AI Data Processing
This paper deals with the concept of cyber intelligence and its components as a fundamental tool for the protection of information today. After that, the main cyber-intelligence frameworks that are currently applied worldwide (Diamond Model, Cyberkill Chain, and Mitre Att&ck) are described to su...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-08-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/16/9328 |
| _version_ | 1797585607109640192 |
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| author | Alberto Sánchez del Monte Luis Hernández-Álvarez |
| author_facet | Alberto Sánchez del Monte Luis Hernández-Álvarez |
| author_sort | Alberto Sánchez del Monte |
| collection | DOAJ |
| description | This paper deals with the concept of cyber intelligence and its components as a fundamental tool for the protection of information today. After that, the main cyber-intelligence frameworks that are currently applied worldwide (Diamond Model, Cyberkill Chain, and Mitre Att&ck) are described to subsequently analyse them through their practical application in a real critical cyber incident, as well as analyse the strengths and weaknesses of each one of them according to the comparison of seventeen variables of interest. From this analysis and considering the two actions mentioned, it is concluded that Mitre Att&ck is the most suitable framework due to its flexibility, permanent updating, and the existence of a powerful database. Finally, an explanation is given for how Mitre Att&ck can be integrated with the research and application of artificial intelligence in the achievement of the objectives set and the development of tools that can serve as support for the detection of the patterns and authorship of cyberattacks. |
| first_indexed | 2024-03-11T00:09:29Z |
| format | Article |
| id | doaj.art-4ea9361d98d74d63948507688acb2925 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T00:09:29Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-4ea9361d98d74d63948507688acb29252023-11-19T00:08:04ZengMDPI AGApplied Sciences2076-34172023-08-011316932810.3390/app13169328Analysis of Cyber-Intelligence Frameworks for AI Data ProcessingAlberto Sánchez del Monte0Luis Hernández-Álvarez1Doctoral School “Studii Salamantini”, Computer Engineering, University of Salamanca, 37008 Salamanca, SpainInstitute for Physical and Information Technologies (ITEFI), Spanish National Research Council (CSIC), 28006 Madrid, SpainThis paper deals with the concept of cyber intelligence and its components as a fundamental tool for the protection of information today. After that, the main cyber-intelligence frameworks that are currently applied worldwide (Diamond Model, Cyberkill Chain, and Mitre Att&ck) are described to subsequently analyse them through their practical application in a real critical cyber incident, as well as analyse the strengths and weaknesses of each one of them according to the comparison of seventeen variables of interest. From this analysis and considering the two actions mentioned, it is concluded that Mitre Att&ck is the most suitable framework due to its flexibility, permanent updating, and the existence of a powerful database. Finally, an explanation is given for how Mitre Att&ck can be integrated with the research and application of artificial intelligence in the achievement of the objectives set and the development of tools that can serve as support for the detection of the patterns and authorship of cyberattacks.https://www.mdpi.com/2076-3417/13/16/9328artificial intelligenceCyberkill Chaincyber intelligenceDiamond Modelindicators of compromisemachine learning |
| spellingShingle | Alberto Sánchez del Monte Luis Hernández-Álvarez Analysis of Cyber-Intelligence Frameworks for AI Data Processing Applied Sciences artificial intelligence Cyberkill Chain cyber intelligence Diamond Model indicators of compromise machine learning |
| title | Analysis of Cyber-Intelligence Frameworks for AI Data Processing |
| title_full | Analysis of Cyber-Intelligence Frameworks for AI Data Processing |
| title_fullStr | Analysis of Cyber-Intelligence Frameworks for AI Data Processing |
| title_full_unstemmed | Analysis of Cyber-Intelligence Frameworks for AI Data Processing |
| title_short | Analysis of Cyber-Intelligence Frameworks for AI Data Processing |
| title_sort | analysis of cyber intelligence frameworks for ai data processing |
| topic | artificial intelligence Cyberkill Chain cyber intelligence Diamond Model indicators of compromise machine learning |
| url | https://www.mdpi.com/2076-3417/13/16/9328 |
| work_keys_str_mv | AT albertosanchezdelmonte analysisofcyberintelligenceframeworksforaidataprocessing AT luishernandezalvarez analysisofcyberintelligenceframeworksforaidataprocessing |