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Effective techniques to identify and stop security breaches are becoming more and more necessary as cyberattacks become more frequent and sophisticated. Because machine learning (ML) can evaluate vast volumes of data and spot patterns that are hard for people to see, it has become a promising tool for network security. The reason of this study article is to scrutinize the ideas, methods; efficacy, hazards, and difficulties associated with machine learning (ML) and analyze how they affect network security.

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Practical Methods to Use Promising Network Security Tools to Analyze and Detect the Impact of Machine Learning Affects

  • 会议论文

  • 发表日期：

    2025年

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  • Chandrugonda Malleshwar Rao,
  • Botcha Kishore Kumar,
  • B. Kavitha Rani,
  • B. Sekhar,
  • B. Gayathri,
  • Ch. Rajakishore Babu

摘要

Effective techniques to identify and stop security breaches are becoming more and more necessary as cyberattacks become more frequent and sophisticated. Because machine learning (ML) can evaluate vast volumes of data and spot patterns that are hard for people to see, it has become a promising tool for network security. The reason of this study article is to scrutinize the ideas, methods; efficacy, hazards, and difficulties associated with machine learning (ML) and analyze how they affect network security.