Empirical results on firewall access with different actions were compared against six benchmark classification algorithms, namely, SVM, OneR, ANN, Multi class classifier, PSO and ZeroR, in five popular evaluation metrics. In this study, a decision tree classification algorithm with a tree-structured model is used for firewall activity analysis, which produces high classification accuracy. However, the output models (i.e., classification models) lack explanatory power insight into the relative influence of the main factors in the classification and thus have low accuracy. Machine learning algorithms are used for Repeated Stemanalysis of the activities on firewall devices and to control traffic on the basis of the results. Incoming and outgoing Internet traffic are controlled using a firewall through an automated Internet security system using a predefined set of rules. Therefore, analyzing the behavior of Internet traffic manually is not possible due to its complexity and the large number of user activity. As Internet usage becomes pervasive, attacks against them are also rising aiming to penetrate the target network and remain undiscovered. Internet usage is increasing rapidly worldwide, allowing numerous connected computer objects or devices to run and communicate with mass digital information.
0 Comments
Leave a Reply. |