The Faculty of Computer Science and Information Technology discussed the master's thesis entitled "Machine Learning Algorithms for Intrusion Detection Systems" by student Inaam Abdullah Abdul Majeed and supervised by Dr. Idris Mohamed Hussein. Machine learning using the hybrid CNN-LSTM architecture, as it follows a new approach to create a new data set resulting from merging two data sets and then using the cross-assessment strategy for data sets to examine the performance of the system. The combined data versus the use of individual data sets, especially when conducting transient assessments of data sets, as well as overcoming the generalization problem raised in previous articles. The traditional intrusion detection system as a front end and employing the . system Suggested machine learning to monitor and evaluate front end performance.