Enhancing Network Intrusion Recovery in SDN with machine learning: an innovative approach
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Enhancing Network Intrusion Recovery in SDN with machine learning: an innovative approach
Authors
Keywords
-
Journal
Arab Journal of Basic and Applied Sciences
Volume 30, Issue 1, Pages 561-572
Publisher
Informa UK Limited
Online
2023-09-25
DOI
10.1080/25765299.2023.2261219
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Supervised machine learning for jamming transition in traffic flow with fluctuations in acceleration and braking
- (2023) Naveed Ahmad Khan et al. COMPUTERS & ELECTRICAL ENGINEERING
- Learning-Based Methods for Cyber Attacks Detection in IoT Systems: A Survey on Methods, Analysis, and Future Prospects
- (2022) Usman Inayat et al. Electronics
- IoTBoT-IDS: A novel statistical learning-enabled botnet detection framework for protecting networks of smart cities
- (2021) Javed Ashraf et al. Sustainable Cities and Society
- Software-Defined Networking Approaches for Link Failure Recovery: A Survey
- (2020) Jehad Ali et al. Sustainability
- Data Mining and Machine Learning Methods for Sustainable Smart Cities Traffic Classification: A Survey
- (2020) Muhammad Shafiq et al. Sustainable Cities and Society
- A deep learning-based IoT-oriented infrastructure for secure smart City
- (2020) Sushil Kumar Singh et al. Sustainable Cities and Society
- Cyber security in smart cities: A review of deep learning-based applications and case studies
- (2020) Dongliang Chen et al. Sustainable Cities and Society
- Fault Detection in Wireless Sensor Networks through the Random Forest Classifier
- (2019) Zainib Noshad et al. SENSORS
- Machine Learning-Based Link Fault Identification and Localization in Complex Networks
- (2019) Srinikethan Madapuzi Srinivasan et al. IEEE Internet of Things Journal
- Software-defined wireless sensor networks in smart grids: An overview
- (2019) Mohammad Abujubbeh et al. Sustainable Cities and Society
- VARMAN: Multi-plane security framework for software defined networks
- (2019) Prabhakar Krishnan et al. COMPUTER COMMUNICATIONS
- Applying Event Stream Processing to Network Online Failure Prediction
- (2018) Juan C. Duenas et al. IEEE COMMUNICATIONS MAGAZINE
- Machine Learning for Networking: Workflow, Advances and Opportunities
- (2018) Mowei Wang et al. IEEE NETWORK
- A Survey of Machine Learning Techniques Applied to Self-Organizing Cellular Networks
- (2017) Paulo Valente Klaine et al. IEEE Communications Surveys and Tutorials
- Software Defined Networking for Improved Wireless Sensor Network Management: A Survey
- (2017) Musa Ndiaye et al. SENSORS
- Link Failure Recovery Using Shortest Path Fast Rerouting Technique in SDN
- (2017) V. Muthumanikandan et al. WIRELESS PERSONAL COMMUNICATIONS
- Big Data for Autonomic Intercontinental Overlays
- (2016) Olivier Brun et al. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
- A Survey on Software Defined Networking: Architecture for Next Generation Network
- (2016) Sanjeev Singh et al. Journal of Network and Systems Management
- Software-defined networking: management requirements and challenges
- (2015) Juliano Wickboldt et al. IEEE COMMUNICATIONS MAGAZINE
- A roadmap for traffic engineering in SDN-OpenFlow networks
- (2014) Ian F. Akyildiz et al. Computer Networks
- A Survey on Software-Defined Network and OpenFlow: From Concept to Implementation
- (2014) Fei Hu et al. IEEE Communications Surveys and Tutorials
- Network Innovation using OpenFlow: A Survey
- (2013) Adrian Lara et al. IEEE Communications Surveys and Tutorials
- OpenFlow
- (2008) Nick McKeown et al. ACM SIGCOMM Computer Communication Review
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started