Artificial Intelligence in Cybersecurity: A Comprehensive Review and Future Direction DOI Creative Commons
Lizzy Oluwatoyin Ofusori, Tebogo Bokaba, Siyabonga Mhlongo

и другие.

Applied Artificial Intelligence, Год журнала: 2024, Номер 38(1)

Опубликована: Дек. 10, 2024

As cybercrimes are becoming increasingly complex, it is imperative for cybersecurity measures to become more robust and sophisticated. The crux lies in extracting patterns or insights from data build data-driven models, thus making the security systems automated intelligent. To comprehend analyze data, several Artificial Intelligence (AI) methods such as Machine Learning (ML) techniques, employed monitor network environments actively combat cyber threats. This study explored various AI techniques how they applied cybersecurity. A comprehensive literature review was conducted, including a bibliometric analysis systematic following PRISMA (Preferred Reporting Items Systematic Reviews Meta-Analyses) guidelines. Using extracted two main scholarly databases: Clarivate's Web of Science (WoS) Scopus, this article examines relevant academic understand diverse ways which strengthen measures. These applications range anomaly detection threat identification predictive analytics incident response. total 14,509 peer-reviewed research papers were identified 9611 Scopus database 4898 WoS database. further filtered, 939 eventually selected used. offers into effectiveness, challenges, emerging trends utilizing purposes.

Язык: Английский

A Comprehensive Machine Learning Approach for COVID-19 Target Discovery in the Small-Molecule Metabolome DOI Creative Commons
Md. Shaheenur Islam Sumon,

Md. Sakib Abrar Hossain,

Haya Al‐Sulaiti

и другие.

Metabolites, Год журнала: 2025, Номер 15(1), С. 44 - 44

Опубликована: Янв. 11, 2025

Background/Objectives: Respiratory viruses, including Influenza, RSV, and COVID-19, cause various respiratory infections. Distinguishing these viruses relies on diagnostic methods such as PCR testing. Challenges stem from overlapping symptoms the emergence of new strains. Advanced diagnostics are crucial for accurate detection effective management. This study leveraged nasopharyngeal metabolome data to predict virus scenarios control vs. Influenza A, all COVID-19 A/RSV. Method: We proposed a stacking-based ensemble technique, integrating top three best-performing ML models initial results enhance prediction accuracy by leveraging strengths multiple base learners. Key techniques feature ranking, standard scaling, SMOTE were used address class imbalances, thus enhancing model robustness. SHAP analysis identified metabolites influencing positive predictions, thereby providing valuable insights into markers. Results: Our approach not only outperformed existing but also revealed dominant features predicting Lysophosphatidylcholine acyl C18:2, Kynurenine, Phenylalanine, Valine, Tyrosine, Aspartic Acid (Asp). Conclusions: demonstrates effectiveness scenarios. The enhances accuracy, provides key markers, offers robust framework managing

Язык: Английский

Процитировано

1
Artificial Intelligence in Cybersecurity: A Comprehensive Review and Future Direction DOI Creative Commons
Lizzy Oluwatoyin Ofusori, Tebogo Bokaba, Siyabonga Mhlongo

и другие.

Applied Artificial Intelligence, Год журнала: 2024, Номер 38(1)

Опубликована: Дек. 10, 2024

As cybercrimes are becoming increasingly complex, it is imperative for cybersecurity measures to become more robust and sophisticated. The crux lies in extracting patterns or insights from data build data-driven models, thus making the security systems automated intelligent. To comprehend analyze data, several Artificial Intelligence (AI) methods such as Machine Learning (ML) techniques, employed monitor network environments actively combat cyber threats. This study explored various AI techniques how they applied cybersecurity. A comprehensive literature review was conducted, including a bibliometric analysis systematic following PRISMA (Preferred Reporting Items Systematic Reviews Meta-Analyses) guidelines. Using extracted two main scholarly databases: Clarivate's Web of Science (WoS) Scopus, this article examines relevant academic understand diverse ways which strengthen measures. These applications range anomaly detection threat identification predictive analytics incident response. total 14,509 peer-reviewed research papers were identified 9611 Scopus database 4898 WoS database. further filtered, 939 eventually selected used. offers into effectiveness, challenges, emerging trends utilizing purposes.

Язык: Английский

Процитировано

2