IoT data feature extraction and intrusion detection system for smart cities based on deep migration learning-Reference-Cited by-同舟云学术

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IoT data feature extraction and intrusion detection system for smart cities based on deep migration learning

Published:2019-12 Issue: Volume:49 Page:533-545
ISSN:0268-4012
Container-title:International Journal of Information Management
language:en
Short-container-title:International Journal of Information Management

Author:

Li Daming,Deng Lianbing,Lee Minchang,Wang Haoxiang

Funder

National Key R&D Program of China: International cooperation between governments in scientific and technological innovation

China Postdoctoral Science Foundation

Publisher

Elsevier BV

Subject

Library and Information Sciences,Computer Networks and Communications,Information Systems

Reference41 articles.

1. Cloud-based business services innovation: A risk management model;Ali;International Journal of Information Management,2017

2. Computer security threat monitoring and surveillance;Anderson,1980

3. Next generation intrusion detection expert system (NIDES). A summary;Anderson,2019

4. Internet of things networking technology;Anping,2013

5. An introduction to intrusion detection [EB/0L];Aurobindo,2019

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1. Stacked autoencoder with weighted loss function for intrusion detection in IoT application;Multimedia Tools and Applications;2024-08-13

2. Development of novel intrusion detection in Internet of Things using improved dart game optimizer‐derived optimal cascaded ensemble learning;Transactions on Emerging Telecommunications Technologies;2024-07

3. Study for Integrating IoT-IDS Datasets: Machine and Deep Learning for Secure IoT Network System;Proceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering;2024-06-18

4. An effective classification using enhanced elephant herding optimization with convolution neural network for intrusion detection in IoMT architecture;Cluster Computing;2024-06-12

5. Providing a hybrid approach to increase the accuracy of intrusion detection systems in computer networks;Journal of Engineering and Applied Science;2024-05-28

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