{"id":1633,"date":"2022-10-05T00:00:00","date_gmt":"2022-10-05T00:00:00","guid":{"rendered":"https:\/\/uomosul.edu.iq\/en\/computerscience\/2022\/10\/05\/master-dissertation-final-defense-building-a-software-tool-to-detect-network-attacks-using-artificial-intelligence-techniques\/"},"modified":"2023-04-14T21:41:06","modified_gmt":"2023-04-14T21:41:06","slug":"master-dissertation-final-defense-building-a-software-tool-to-detect-network-attacks-using-artificial-intelligence-techniques","status":"publish","type":"post","link":"https:\/\/uomosul.edu.iq\/en\/computerscience\/2022\/10\/05\/master-dissertation-final-defense-building-a-software-tool-to-detect-network-attacks-using-artificial-intelligence-techniques\/","title":{"rendered":"Master\u00a0 Dissertation Final Defense \u201cBuilding a software tool to detect network attacks using artificial intelligence techniques"},"content":{"rendered":"

Master Dissertation Final DefenseAs part of the academic activities of our college, Teba Ali Jassm has successfully passed her Master final defense entitled “Building a software tool to detect network attacks using artificial intelligence techniques” in 5\/10 \/2022.Teba has developed a system that detects network attacks using artificial intelligence techniques. The study dealt with training the Convolutional Neural Networks (CNN) and Long-Term Memory (LSTM) algorithms based on two commonly used and recent data sets in different attack and intrusion detection systems. Training and losing. The study aims to create a software tool that predicts the type of network traffic, whether it is harmful or benignThe scientific committee included the following members:<\/p>\n