A Systematic Literature Review on Host-Based Intrusion Detection Systems
Author:
Affiliation:
1. Department of Computer Engineering, Ondokuz Mayıs University, Samsun, Turkey
2. Department of Computer Engineering, İstinye University, Istanbul, Turkey
3. ASELSAN, Ankara, Turkey
Funder
Scientific and Technological Research Council of Turkey (TUBITAK) Frontier R&D Laboratories Support Program 1515
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10439152.pdf?arnumber=10439152
Reference77 articles.
1. Intrusion detection system: A comprehensive review
2. Host-based IDS: A review and open issues of an anomaly detection system in IoT
3. A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions
4. An effective NIDS framework based on a comprehensive survey of feature optimization and classification techniques
5. Stacking ensemble-based HIDS framework for detecting anomalous system processes in Windows based operating systems using multiple word embedding
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2. Enhancing network attack detection across infrastructures: An automatic labeling method and deep learning model with an attention mechanism;IET Communications;2024-08-22
3. RPL-based attack detection approaches in IoT networks: review and taxonomy;Artificial Intelligence Review;2024-08-12
4. Two-stage multi-datasource machine learning for attack technique and lifecycle detection;Computers & Security;2024-07
5. Feature Selection Using Pearson Correlation with Lasso Regression for Intrusion Detection System;2024 12th International Symposium on Digital Forensics and Security (ISDFS);2024-04-29
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