A New Proposal on the Advanced Persistent Threat: A Survey
An advanced persistent threat (APT) can be defined as a targeted and very sophisticated cyber attack. IT administrators need tools that allow for the early detection of these attacks. Several approaches have been proposed to provide solutions to this problem based on the attack life cycle. Recently,...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/11/3874 |
| _version_ | 1797566211792306176 |
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| author | Santiago Quintero-Bonilla Angel Martín del Rey |
| author_facet | Santiago Quintero-Bonilla Angel Martín del Rey |
| author_sort | Santiago Quintero-Bonilla |
| collection | DOAJ |
| description | An advanced persistent threat (APT) can be defined as a targeted and very sophisticated cyber attack. IT administrators need tools that allow for the early detection of these attacks. Several approaches have been proposed to provide solutions to this problem based on the attack life cycle. Recently, machine learning techniques have been implemented in these approaches to improve the problem of detection. This paper aims to propose a new approach to APT detection, using machine learning techniques, and is based on the life cycle of an APT attack. The proposed model is organised into two passive stages and three active stages to adapt the mitigation techniques based on machine learning. |
| first_indexed | 2024-03-10T19:24:26Z |
| format | Article |
| id | doaj.art-1673a171a4e84a2b8dce5b610584155c |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T19:24:26Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-1673a171a4e84a2b8dce5b610584155c2023-11-20T02:42:05ZengMDPI AGApplied Sciences2076-34172020-06-011011387410.3390/app10113874A New Proposal on the Advanced Persistent Threat: A SurveySantiago Quintero-Bonilla0Angel Martín del Rey1Department of Applied Mathematics, University of Salamanca, 37008 Salamanca, SpainInstitute of Fundamental Physics and Mathematics, Department of Applied Mathematics, University of Salamanca, 37008 Salamanca, SpainAn advanced persistent threat (APT) can be defined as a targeted and very sophisticated cyber attack. IT administrators need tools that allow for the early detection of these attacks. Several approaches have been proposed to provide solutions to this problem based on the attack life cycle. Recently, machine learning techniques have been implemented in these approaches to improve the problem of detection. This paper aims to propose a new approach to APT detection, using machine learning techniques, and is based on the life cycle of an APT attack. The proposed model is organised into two passive stages and three active stages to adapt the mitigation techniques based on machine learning.https://www.mdpi.com/2076-3417/10/11/3874advanced persistent threatsmachine learningmalware detectioncybersecurity |
| spellingShingle | Santiago Quintero-Bonilla Angel Martín del Rey A New Proposal on the Advanced Persistent Threat: A Survey Applied Sciences advanced persistent threats machine learning malware detection cybersecurity |
| title | A New Proposal on the Advanced Persistent Threat: A Survey |
| title_full | A New Proposal on the Advanced Persistent Threat: A Survey |
| title_fullStr | A New Proposal on the Advanced Persistent Threat: A Survey |
| title_full_unstemmed | A New Proposal on the Advanced Persistent Threat: A Survey |
| title_short | A New Proposal on the Advanced Persistent Threat: A Survey |
| title_sort | new proposal on the advanced persistent threat a survey |
| topic | advanced persistent threats machine learning malware detection cybersecurity |
| url | https://www.mdpi.com/2076-3417/10/11/3874 |
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