An advanced filter-based supervised threat detection framework on large databases

HIGHLIGHTS

  • What: A detailed analysis was carried out to investigate the performance of the proposed algorithm and compare it with various machine-learning models. This approach examined a range of variables, including communication styles, access trends, and user behavior, to build cyber-personas or profiles for each member of the business, and then used deep learning methods to detect aberrant behaviors or suspicious activity. This study proposed a generative network to create artificial data that closely resembles actual network Byrapuneni and amp; Saidi Reddy:
  • Who: gerry from the Department of Computer Science and Engineering, Koneru Lakshmaiah . . .

     

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