Conversational Artificial Intelligence-Ch20
學年 112
學期 1
出版（發表）日期 2024-01-27
作品名稱 Conversational Artificial Intelligence-Ch20
作品名稱（其他語言） ChatBot‐Based Next‐Generation Intrusion Detection System
著者 Chen, Tzu-chia
單位
出版者 John Wiley & Sons, Inc.
著錄名稱、卷期、頁數
摘要 An intrusion detection system, often known as IDS, is primarily used to gather and analyze data regarding security events that occur in computer systems and networks. Its subsequent purpose is to either prevent these events from happening or notify them to the administrator of the system. As a result of the increasing number of attacks carried out by attackers, the users’ level of mistrust on the Internet has increased. Attacks that cause denial of service are a major violation of security. This article presents a particle swarm optimization and AdaBoost-based intrusion detection system. In this system, chatbot receives network traffic as input, and features of input dataset are selected using particle swarm optimization algorithm. A classification model is trained and tested. AdaBoost, KNN, and naïve Bayes algorithm are used to classify and detect malware-related records. NSL KDD dataset is used in the experimental work. PSO-AdaBoost achieves the highest accuracy, precision, and recall for intrusion detection and classification. The output of a chatbot is a language that is either normal or benign.
關鍵字
語言 en_US
ISBN 9781394200566
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/125129 )