Anomaly Detection IDS for Detecting DoS Attacks in IoT Networks Based on Machine Learning Algorithms
King Faisal University · University of Jordan · +1 more institution
Abstract
Widespread and ever-increasing cybersecurity attacks against Internet of Things (IoT) systems are causing a wide range of problems for individuals and organizations. The IoT is self-configuring and open, making it vulnerable to insider and outsider attacks. In the IoT, devices are designed to self-configure, enabling them to connect to networks autonomously without extensive manual configuration. By using various protocols, technologies, and automated processes, self-configuring IoT devices are able to seamlessly connect to networks, discover services, and adapt their configurations without requiring manual intervention or setup. Users' security and privacy may be compromised by attackers seeking to obtain…
Citation impact
- FWCI
- 53.51
- Percentile
- 100%
- References
- 40
Authors
3Topics & keywords
- Computer science
- Denial-of-service attack
- Anomaly detection
- Support vector machine
- Computer security
- Feature selection
- Internet of Things
- Machine learning