Deep-IDS: A Real-Time Intrusion Detector for IoT Nodes Using Deep Learning-Reference-Cited by-同舟云学术

Deep-IDS: A Real-Time Intrusion Detector for IoT Nodes Using Deep Learning

Published:2024 Issue: Volume:12 Page:63584-63597
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Racherla Sandeepkumar¹^ORCID,Sripathi Prathyusha¹^ORCID,Faruqui Nuruzzaman²^ORCID,Alamgir Kabir Md³^ORCID,Whaiduzzaman Md⁴^ORCID,Aziz Shah Syed⁵^ORCID

Affiliation:

1. Amazon, Seattle, WA, USA

2. Department of Software Engineering, Daffodil International University, Daffodil Smart City, Birulia, Dhaka, Bangladesh

3. Division of Computer Science and Software Engineering, Mälardalen University, Västerås, Sweden

4. School of Information Systems, Queensland University of Technology, Brisbane, QLD, Australia

5. Centre for Intelligent Healthcare, Coventry University, Coventry, U.K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10518015.pdf?arnumber=10518015

Reference75 articles.

1. Intrusion detection system for large-scale IoT NetFlow networks using machine learning with modified Arithmetic Optimization Algorithm

2. Integration of Cloud, IoT, and AI for Smart Services

3. A Review on Cyber Crimes on the Internet of Things

4. M2VT-IDS: A multi-task multi-view learning architecture for designing IoT intrusion detection system

5. Multi-objective optimization algorithms for intrusion detection in IoT networks: A systematic review

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1. Towards Universal and Transferable Adversarial Attacks against Network Traffic Classification;Computer Networks;2024-09

2. Intrusion Detection System Using Improved Gloden Jackal optimization for Security and Privacy in Internet of Things;2024 Second International Conference on Data Science and Information System (ICDSIS);2024-05-17