Differential Evolution Wrapper Feature Selection for Intrusion Detection System
نویسندگان
چکیده
منابع مشابه
Efficient Feature Selection Technique for Network Intrusion Detection System Using Discrete Differential Evolution and Decision
Network intrusion is a critical challenge in information and communication systems amongst other forms of fraud perpetrated over the Internet. Despite the various traditional techniques proposed to prevent this intrusion, the threat persists. These days, intrusion detection systems (IDS) are faced with detecting attacks in large streams of connections due to the sporadic increase in network tra...
متن کاملFeature Selection Approach for Intrusion Detection System
At present, network security needs to be concerned to provide secure information channels due to increase in potential network attacks. Intrusion Detection System (IDS) is a valuable tool for the defense-in-depth of computer networks. However, building an efficient ID faces a number of challenges. One of the important challenges is dealing with data containing a high number of features. Current...
متن کاملFeature selection for intrusion detection system
Intrusion detection is an important task for network operators in today’s Internet. Traditional network intrusion detection systems rely on either specialized signatures of previously seen attacks, or on labeled traffic datasets that are expensive and difficult to reproduce for user-profiling to hunt out network attacks. Machine learning methods could be used in this area since they could get k...
متن کاملA Parallel Genetic Algorithm Based Method for Feature Subset Selection in Intrusion Detection Systems
Intrusion detection systems are designed to provide security in computer networks, so that if the attacker crosses other security devices, they can detect and prevent the attack process. One of the most essential challenges in designing these systems is the so called curse of dimensionality. Therefore, in order to obtain satisfactory performance in these systems we have to take advantage of app...
متن کاملNovel Multi-Objective Artificial Bee Colony Optimization for Wrapper Based Feature Selection in Intrusion Detection
This study proposes a novel approach based on multi-objective artificial bee colony (ABC) for feature selection, particularly for intrusion-detection systems. The approach is divided into two stages: generating the feature subsets of the Pareto front of non-dominated solutions in the first stage and using the hybrid ABC and particle swarm optimization (PSO) with a feed-forward neural network (F...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2020
ISSN: 1877-0509
DOI: 10.1016/j.procs.2020.03.438