This paper discusses the use of WEKA data analytics technique for intrusion detection and examines the performance of Random Forest and Logistic Regression algorithms. The dataset used is collected from U2R and R2L attacks on networks. The results show that Random Forest outperforms Logistic Regression in terms of classification accuracy, precision, and recall.