Investigating the Impact of Feature Reduction Through Information Gain and Correlation on the Performance of Error Back Propagation Based IDS

Abstract

Research in the field of IDS has been going on since long time; however, there exists a number of ways to further improve the efficiency of IDS. This paper investigates the performance of Intrusion detection system using feature reduction and EBPA. The first step involves the reduction in number of features, based on the combination of information gain and correlation. In the next step, error back propagation algorithm (EBPA) is used to train the network and then analyze the performance. EBPA is commonly used due to its ease of use, high accuracy and efficiency. The proposed model is tested over the KDD Cup 99 and NSL-KDD datasets. Results show that the proposed IDS model with reduced feature set outperforms the other models, both in terms of performance metrics and processing time.

IoT Security Framework Optimized Evaluation for Smart Grid

“…IoT Here's a comparative analysis table described in table 1 summarizing the key concepts covered and concepts not covered in the existing articles related to the security of smart grid IoTs that we provided: Figure 1 shows conceptual framework that can be used to guide the security advance of IoT smart grid architecture. Our framework can be used to detect the potential vulnerabilities and the applicable mitigation mechanism [21].…”