“A Novel Model for Detecting Distributed Denial of Service (DDoS) Attack in Software-Defined Networking Using Artificial Intelligence Techniques”
Country of Study
Kenya
Institution
Pan African University Institute for Basic Sciences, Technology and Innovation
Expected Year of Completion
2024
Thematic Area
Information and Technology
Education
Aminata is pursuing a PhD in Electrical Engineering, at the Pan African University Institute for Basic Sciences, Technology and Innovation(PAUSTI) in Kenya and works as a Communication Officer at the African Union Commission. She has an MSc in Network and Telecommunication from Sup’ Management Mali University and is expected to complete her studies in 2024.
Research Summary
Centralised control is the target of many attacks that pose a security problem to the proper functioning of Software Defining Network (SDN) technology. The most common attacks taking place in the SDN controllers include distributed denial of service (DDoS). As the name implies, a denial-of-service attack is an attempt by attackers to keep users from accessing a network system, service, website, application, or other resources. The attack typically makes a system slow to respond, or it can disable the system entirely. An attack that originates from a single source is simply a denial-of-service (DoS) attack. However, far more common today are distributed denial-of-service (DDoS) attacks, which are launched at a target from multiple sources but coordinated from a central point. Distributed attacks are larger, potentially more devastating, and in some cases more difficult for the victim to detect and stop. Aminata’s area of research is very important because technology is evolving very fast and there are great innovations but which, ironically, are also vulnerable to several security issues that need to be addressed for the protection of personal data. Many researchers have proposed several methods of detecting DDoS attacks, but most of them focus on detecting and mitigating the attack once it has occurred in the controller which needs to be improved. The contribution of this research would be to apply artificial intelligence to innovate the intrusion attack detection technique in SDN.
