Current trends in AI and ML for cybersecurity: A state-of-the-art survey
AbstractThis paper provides a comprehensive survey of the state-of-the-art use of Artificial Intelligence (AI) and Machine Learning (ML) in the field of cybersecurity. The paper illuminates key applications of AI and ML in cybersecurity, while also addressing existing challenges and posing unresolve...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2023-12-01
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| Series: | Cogent Engineering |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/23311916.2023.2272358 |
| _version_ | 1797258409584623616 |
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| author | Nachaat Mohamed |
| author_facet | Nachaat Mohamed |
| author_sort | Nachaat Mohamed |
| collection | DOAJ |
| description | AbstractThis paper provides a comprehensive survey of the state-of-the-art use of Artificial Intelligence (AI) and Machine Learning (ML) in the field of cybersecurity. The paper illuminates key applications of AI and ML in cybersecurity, while also addressing existing challenges and posing unresolved questions for future research. The paper also emphasizes the ethical and legal implications associated with their implementation. The researchers conducted a thorough survey by reviewing numerous papers and articles from respected sources such as IEEE, ACM, and Springer. Their focus centered on the latest AI and ML breakthroughs in cybersecurity, while also exploring current challenges and open research questions. The results indicate that integrating AI and ML into cybersecurity systems shows great potential for future research and development. Intrusion detection and response, malware detection, and network security are among the most promising applications identified. According to the survey, 45% of organizations have already implemented AI and ML in their cybersecurity systems, while an additional 35% plan to do so. However, 20% of organizations believe that it is not yet the right time for adopting these technologies. Overall, this paper serves as a reliable reference for researchers and practitioners in the field of cybersecurity, offering a comprehensive overview of the use of AI and ML. It not only highlights the potential applications but also addresses the challenges and research gaps. Additionally, the paper raises awareness about the ethical and legal considerations associated with leveraging AI and ML in the cybersecurity domain. |
| first_indexed | 2024-03-08T23:54:11Z |
| format | Article |
| id | doaj.art-e469c4620e884e16b3420334c827b926 |
| institution | Directory Open Access Journal |
| issn | 2331-1916 |
| language | English |
| last_indexed | 2024-04-24T22:53:05Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Engineering |
| spelling | doaj.art-e469c4620e884e16b3420334c827b9262024-03-18T10:22:11ZengTaylor & Francis GroupCogent Engineering2331-19162023-12-0110210.1080/23311916.2023.2272358Current trends in AI and ML for cybersecurity: A state-of-the-art surveyNachaat Mohamed0Rabdan Academy, (Homeland Security Department), Abu Dhabi, UAEAbstractThis paper provides a comprehensive survey of the state-of-the-art use of Artificial Intelligence (AI) and Machine Learning (ML) in the field of cybersecurity. The paper illuminates key applications of AI and ML in cybersecurity, while also addressing existing challenges and posing unresolved questions for future research. The paper also emphasizes the ethical and legal implications associated with their implementation. The researchers conducted a thorough survey by reviewing numerous papers and articles from respected sources such as IEEE, ACM, and Springer. Their focus centered on the latest AI and ML breakthroughs in cybersecurity, while also exploring current challenges and open research questions. The results indicate that integrating AI and ML into cybersecurity systems shows great potential for future research and development. Intrusion detection and response, malware detection, and network security are among the most promising applications identified. According to the survey, 45% of organizations have already implemented AI and ML in their cybersecurity systems, while an additional 35% plan to do so. However, 20% of organizations believe that it is not yet the right time for adopting these technologies. Overall, this paper serves as a reliable reference for researchers and practitioners in the field of cybersecurity, offering a comprehensive overview of the use of AI and ML. It not only highlights the potential applications but also addresses the challenges and research gaps. Additionally, the paper raises awareness about the ethical and legal considerations associated with leveraging AI and ML in the cybersecurity domain.https://www.tandfonline.com/doi/10.1080/23311916.2023.2272358AIMLcybersecurityintrusion detectionmalware detectionnetwork security |
| spellingShingle | Nachaat Mohamed Current trends in AI and ML for cybersecurity: A state-of-the-art survey Cogent Engineering AI ML cybersecurity intrusion detection malware detection network security |
| title | Current trends in AI and ML for cybersecurity: A state-of-the-art survey |
| title_full | Current trends in AI and ML for cybersecurity: A state-of-the-art survey |
| title_fullStr | Current trends in AI and ML for cybersecurity: A state-of-the-art survey |
| title_full_unstemmed | Current trends in AI and ML for cybersecurity: A state-of-the-art survey |
| title_short | Current trends in AI and ML for cybersecurity: A state-of-the-art survey |
| title_sort | current trends in ai and ml for cybersecurity a state of the art survey |
| topic | AI ML cybersecurity intrusion detection malware detection network security |
| url | https://www.tandfonline.com/doi/10.1080/23311916.2023.2272358 |
| work_keys_str_mv | AT nachaatmohamed currenttrendsinaiandmlforcybersecurityastateoftheartsurvey |