What question did this study set out to answer?

To review the application, effectiveness, and limitations of machine learning methods used to detect malware and mitigate modern cybersecurity threats.

July 10, 2022Journal of Cybersecurity and PrivacyOpen Access

Cybersecurity Threats and Their Mitigation Approaches Using Machine Learning—A Review

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Authors

MAMostofa AhsanDakota State University KNKendall E. NygardNorth Dakota State University RGRahul GomesUniversity of Wisconsin–Eau Claire

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Implication

Review reveals machine learning approaches for mitigating malware in digital networks, highlighting persistent vulnerabilities in automated threat detection.

Key Points

To review the application, effectiveness, and limitations of machine learning methods used to detect malware and mitigate modern cybersecurity threats.
Evaluated machine learning and statistical classification approaches, including deep learning, support vector machines, and Bayesian classification, applied to cybersecurity network data.
Examined changes in attack patterns over the past decade and assessed existing model architectures for scalable, automated threat detection.
Machine learning models provide superior scalability and actionable threat detection compared to traditional methods by extracting hidden patterns from complex network traffic.
Current state-of-the-art security models exhibit notable shortcomings in defending against rapidly evolving and novel malware attack vectors.

Cite This Study

Ahsan et al. (2022) studied this question.

synapsesocial.com/papers/6a08be6a5686deba6901e514 https://doi.org/10.3390/jcp2030027

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Implication

Review reveals machine learning approaches for mitigating malware in digital networks, highlighting persistent vulnerabilities in automated threat detection.

Cybersecurity Threats and Their Mitigation Approaches Using Machine Learning—A Review

Discussion

Member takes

Implication

Key Points

Cite This Study

Cybersecurity Threats and Their Mitigation Approaches Using Machine Learning—A Review

Discussion

Member takes

Implication

Key Points

Cite This Study

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