Scalable anomaly-based intrusion detection for secure Internet of Things using generative adversarial networks in fog environment
出版年份 2023 全文链接
标题
Scalable anomaly-based intrusion detection for secure Internet of Things using generative adversarial networks in fog environment
作者
关键词
-
出版物
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
Volume 214, Issue -, Pages 103622
出版商
Elsevier BV
发表日期
2023-03-12
DOI
10.1016/j.jnca.2023.103622
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- USMD: UnSupervised Misbehaviour Detection for Multi-Sensor Data
- (2022) Abdullah Alsaedi et al. IEEE Transactions on Dependable and Secure Computing
- Machine learning techniques in emerging cloud computing integrated paradigms: A survey and taxonomy
- (2022) Dinesh Soni et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Fast Anomaly Identification Based on Multiaspect Data Streams for Intelligent Intrusion Detection Toward Secure Industry 4.0
- (2022) Lianyong Qi et al. IEEE Transactions on Industrial Informatics
- A deep density based and self-determining clustering approach to label unknown traffic
- (2022) Mehrnoosh Monshizadeh et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- An optimized ensemble prediction model using AutoML based on soft voting classifier for network intrusion detection
- (2022) Murad Ali Khan et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- The theoretical research of generative adversarial networks: an overview
- (2021) Yanchun Li et al. NEUROCOMPUTING
- DAD: A Distributed Anomaly Detection system using ensemble one-class statistical learning in edge networks
- (2021) Nour Moustafa et al. Future Generation Computer Systems-The International Journal of eScience
- ADEPT: Detection and Identification of Correlated Attack Stages in IoT Networks
- (2021) Kalupahana Liyanage Kushan Sudheera et al. IEEE Internet of Things Journal
- Prepare for trouble and make it double! Supervised – Unsupervised stacking for anomaly-based intrusion detection
- (2021) Tommaso Zoppi et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- RANet: Network intrusion detection with group-gating convolutional neural network
- (2021) Xiaoqing Zhang et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- MTH-IDS: A Multitiered Hybrid Intrusion Detection System for Internet of Vehicles
- (2021) Li Yang et al. IEEE Internet of Things Journal
- Intrusion Detection for Secure Social Internet of Things Based on Collaborative Edge Computing: A Generative Adversarial Network-Based Approach
- (2021) Laisen Nie et al. IEEE Transactions on Computational Social Systems
- On the Performance of Machine Learning Models for Anomaly-Based Intelligent Intrusion Detection Systems for the Internet of Things
- (2021) Ghada Abdelmoumin et al. IEEE Internet of Things Journal
- ADRIoT: An Edge-Assisted Anomaly Detection Framework Against IoT-Based Network Attacks
- (2021) Ruoyu Li et al. IEEE Internet of Things Journal
- A network intrusion detection method based on semantic Re-encoding and deep learning
- (2020) Zhendong Wu et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Increasing the Trustworthiness in the Industrial IoT Networks Through a Reliable Cyberattack Detection Model
- (2020) Mohammad Mehedi Hassan et al. IEEE Transactions on Industrial Informatics
- An In-Depth Analysis of IoT Security Requirements, Challenges, and Their Countermeasures via Software-Defined Security
- (2020) Waseem Iqbal et al. IEEE Internet of Things Journal
- Omni SCADA Intrusion Detection Using Deep Learning Algorithms
- (2020) Jun Gao et al. IEEE Internet of Things Journal
- Mobile Edge Computing Enabled 5G Health Monitoring for Internet of Medical Things: A Decentralized Game Theoretic Approach
- (2020) Zhaolong Ning et al. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
- CorrAUC: A Malicious Bot-IoT Traffic Detection Method in IoT Network Using Machine-Learning Techniques
- (2020) Muhammad Shafiq et al. IEEE Internet of Things Journal
- An Adaptive Trust Boundary Protection for IIoT Networks Using Deep-Learning Feature-Extraction-Based Semisupervised Model
- (2020) Mohammad Mehedi Hassan et al. IEEE Transactions on Industrial Informatics
- Variational LSTM Enhanced Anomaly Detection for Industrial Big Data
- (2020) Xiaokang Zhou et al. IEEE Transactions on Industrial Informatics
- Intrusion Detection for Cyber–Physical Systems Using Generative Adversarial Networks in Fog Environment
- (2020) Paulo Freitas de Araujo-Filho et al. IEEE Internet of Things Journal
- Deep-IFS: Intrusion Detection Approach for Industrial Internet of Things Traffic in Fog Environment
- (2020) Mohamed Abdel-Basset et al. IEEE Transactions on Industrial Informatics
- Deep Learning-Enabled Threat Intelligence Scheme in the Internet of Things Networks
- (2020) Muna Al-Hawawreh et al. IEEE Transactions on Network Science and Engineering
- Learning Latent Representation for IoT Anomaly Detection
- (2020) Ly Vu et al. IEEE Transactions on Cybernetics
- Improving IoT Botnet Investigation Using an Adaptive Network Layer
- (2019) João Ceron et al. SENSORS
- Application of Deep Learning to Cybersecurity: A Survey
- (2019) Samaneh Mahdavifar et al. NEUROCOMPUTING
- Unsupervised learning approach for network intrusion detection system using autoencoders
- (2019) Hyunseung Choi et al. JOURNAL OF SUPERCOMPUTING
- f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks
- (2019) Thomas Schlegl et al. MEDICAL IMAGE ANALYSIS
- Securing Fog Computing for Internet of Things Applications: Challenges and Solutions
- (2018) Jianbing Ni et al. IEEE Communications Surveys and Tutorials
- Learning Neural Representations for Network Anomaly Detection
- (2018) Van Loi Cao et al. IEEE Transactions on Cybernetics
- Representation Learning: A Review and New Perspectives
- (2013) Y. Bengio et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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