"A Model to Classify Cyberattacks Using Swarm Intelligence"

A team of researchers at Glasgow Caledonian University and COMSATS University in Pakistan developed a new intrusion detection scheme to improve the security of information shared via the internet. The proposed scheme is based on the Artificial Bee Colony (ABC) algorithm and the Random Neural Network (RNN-ABC). The intrusion detection RNN-ABC scheme was trained on the NSL-KDD Train+ dataset, which is a dataset used in the training of algorithms to identify the performance of cyberattacks. According to researchers, their scheme has been successful at classifying novel cyberattacks with an accuracy of 91.65%. This article continues to discuss the intrusion detection RNN-ABC scheme in relation to its level of accuracy and how it compares with an existing intrusion detection system based on Hybrid Multilayer Perceptron (MLP), along with the security threat posed by the growth of Internet of Things (IoT) devices. 

TechXplore reports "A Model to Classify Cyberattacks Using Swarm Intelligence"