Abstract
Building a good IDS model from a certain dataset is one of the main tasks in machine learning. Training multiple classifiers at the same time to solve the same problem and then combining their outputs to improve classification quality, called ensemble method. This paper analyzes and evaluates the
Highlights
For companies that are constantly connected to the internet in today’s technology age, the terms DoS and DDoS are not too strange
In this paper we evaluated and analyzed six different ensemble classifier techniques, called Bagging, AdaBoost, Stacking, Decorate, Random Forest and Voting, using various basic classifiers such as Decision Trees (DT), Naive Bayes (NB), Logistic Regression (LR), Support Vector Machine (SVM), k nearest neighbors (KNN) and Random Tree (RT); These were applied on the UNSW-NB15 dataset
RT usually refer to randomly constructed trees that have nothing to do with machine learning
Summary
For companies that are constantly connected to the internet in today’s technology age, the terms DoS and DDoS are not too strange. In recent years, news that the information and technology division of large organizations around the world has been hacked and the stolen data always contains the terms DoS and DDoS. The full name of "DoS" is "Denial of Service" and DDoS is "Distributed Denial of Service", is a form of denial of service attack. This is a fairly common form of attack today, it makes the target computer can not handle the task and lead to overload. These DoS attacks often target virtual servers (VPS) or web servers of large businesses such as banks, governments or e-commerce websites,. Johnson Singh et al [2] claimed that 540Gbps
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: EAI Endorsed Transactions on Context-aware Systems and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
