Classifying DDoS Attack in Industrial Internet of Services Using Machine Learning
- Publisher:
- IEEE
- Publication Type:
- Conference Proceeding
- Citation:
- 2023 15th International Conference on Computer and Automation Engineering (ICCAE), 2023, 00, pp. 546-550
- Issue Date:
- 2023-05-03
Closed Access
| Filename | Description | Size | |||
|---|---|---|---|---|---|
| Classification_of_DDoS_traffic_for_Industrial_Internet_of_Services_using_Deep_learning_approaches.pdf | Published version | 4.49 MB |
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
There were various research articles proposed different IIoT and Industrial Internet of Services IIoS techniques for Industry 4 0 innovative practices At the same time the concept of IIoS is considered a critical enabler for smart industries Therefore IIoT has evolved over time into an IIoS which introduces servitization processes to measure product or service quality The idea behind IIoS is to strategically use the Internet as a platform to assemble new value for the services sector in different industries The IIoS is a vital aspect to consider for improving the final production line However at the same time the internet s inherent vulnerability puts it at risk of cyber security attacks particularly DDoS attacks This research is focused on investigating DDoS vulnerabilities that can negatively impact IIoS The study evaluates six machine learning algorithms in terms of their ability to detect DDoS attacks The mentioned ML algorithms are renowned for data traffic classification within the existing literature Moreover this research can assist users in diagnosing potential DDoS threats and optimizing production lines
Please use this identifier to cite or link to this item: