Design of Multilevel Hybrid Classifier with Variant Feature Sets for Intrusion Detection System
نویسندگان
چکیده
منابع مشابه
Hybrid Feature Selection Algorithm for Intrusion Detection System
Network security is a serious global concern. Usefulness Intrusion Detection Systems (IDS) are increasing incredibly in Information Security research using Soft computing techniques. In the previous researches having irrelevant and redundant features are recognized causes of increasing the processing speed of evaluating the known intrusive patterns. In addition, an efficient feature selection m...
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Intrusions detection systems (IDSs) are systems that try to detect attacks as they occur or after the attacks took place. IDSs collect network traffic information from some point on the network or computer system and then use this information to secure the network. Intrusion detection systems can be misuse-detection or anomaly detection based. Misuse-detection based IDSs can only detect known a...
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Nowadays, as most of the companies and organizations rely on the database to safeguard sensitive data, it is required to guarantee the strong protection of the data. Intrusion detection system (IDS) can be an important component of the strong security framework, and the machine learning approach with adaptation capability has a great advantage for this system. In this paper, we propose a hybrid...
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This paper proposes Hybrid Feature Selection Approach – Heterogeneous Ensemble of Intelligent Classifiers (HyFSA-HEIC) for intelligent lightweight network intrusion detection system (NIDS). The purpose is to classify for anomaly from the incoming traffic. This system hierarchically integrates HyFSA and HEIC. The HyFSA will obtain the optimal number of features and then HEIC is built using these...
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ژورنال
عنوان ژورنال: IEICE Transactions on Information and Systems
سال: 2016
ISSN: 0916-8532,1745-1361
DOI: 10.1587/transinf.2015edp7357