Securing E-Governance Services Based on Two Level Classification Algorithms

Abstract

Due to the expansion of cybercrime and cyberwarfare, the necessity for cyber security has recently expanded substantially. There are several trends in cyber security, but the most important is e-governance. E-government is regarded as one of the most essential platforms for transmitting data and services over the internet that frequently contain valuable and confidential data, making them subject to threats. The majority of egovernance systems rely on public-use services. The paper proposed a framework to detect threats in internet traffic flows. This paper uses a famous dataset that was collected from internet traffic called the UNSW-NB15 dataset, which consists of 307,099 instances. The framework consists of several steps, including pre-processing, identifying a correlation between features, and selecting the best ones. Finally, different machine learning algorithms are used to distinguish the normal traffic from the malware traffic. The findings uncover that SVM achieved very high accuracy (99.16%). Additionally, in the second part, which is called multi-class and consists of two stages, in the first one the study classified the abnormal flows into nine attacks with a lower accuracy of 77.80%. In the second stage with binary classification, the dataset contained both normal and abnormal, and the accuracy improved significantly to 97.48% for SVM.

Analysis of Regional Potential in Merauke Regency Based on Superior Livestock Population Using a Hybrid Algorithm

“…The object is classified to find groups from a set of points, patterns, or entities, to get more in-depth information about the data, to look for similarities, and to map objects to certain groups [4]. Clustering is a process to obtain results from partitions in a data set [5], which are mapped into a group based on their level of similarity [6]. Hierarchical grouping uses a hierarchical (level) arrangement model in the data set based on the characteristics of the data [7], which are then grouped into a cluster [8].…”