Scholarlink

Machine Learning (ML) and Artificial Intelligence (AI) have shown great promise in several areas of cybersecurity. They can learn from patterns, make predictions, and adapt to new situations, making them ideal for identifying threats, detecting anomalies, and discovering intrusions. ML and AI techniques can enhance threat detection in cybersecurity through anomaly detection, predictive analytics, automated threat hunting, phishing detection, malware detection, and user behavior analytics. In this article, we investigate how ML and AI could be integrated to detect Phishing, Malware, Insider Threats and Intrusion Detections. We also study several real-life cases that utilize ML and AI to enhance cybersecurity. Finally, we present a prototype of an ML- and AI-based cybersecurity system.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Harnessing Machine Learning and Artificial Intelligence in Cyber Security: A Deep Dive into Threat Detection, Anomaly Detection, Intrusion Detection, and Malware Analysis

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • David Dorsaima,
  • Lisa Kovalchick,
  • Weifeng Chen

摘要

Machine Learning (ML) and Artificial Intelligence (AI) have shown great promise in several areas of cybersecurity. They can learn from patterns, make predictions, and adapt to new situations, making them ideal for identifying threats, detecting anomalies, and discovering intrusions. ML and AI techniques can enhance threat detection in cybersecurity through anomaly detection, predictive analytics, automated threat hunting, phishing detection, malware detection, and user behavior analytics. In this article, we investigate how ML and AI could be integrated to detect Phishing, Malware, Insider Threats and Intrusion Detections. We also study several real-life cases that utilize ML and AI to enhance cybersecurity. Finally, we present a prototype of an ML- and AI-based cybersecurity system.