Abstract
Digital Twin (DT) technology is a digital illustration of a physical object or system; this technology has paid much attention to IoT, healthcare, automotive manufacturing, construction of buildings, and even cities. However, these applications may also have serious security pitfalls in DT deployment. Distributed Denial of Service (DDoS) attacks significantly threaten the availability and stability of computer networks and services. Detecting and mitigating these attacks on time is crucial for maintaining network security. This chapter aims to develop an algorithmic-based approach for detecting and preventing DDoS attacks in the initial stages of Network Function Virtualisation (NFV). The proposed model involves the Network traffic collected from a sender in various monitoring points within the network infrastructure. Then the traffic is analysed by extracting relevant information like from which source the traffic is coming, Transmission Control Protocol (TCP), three-way handshake details, packet size, and traffic volume. The developed model is deployed in real time to monitor incoming network traffic. It analyses the extracted features and compares them with the learned patterns to identify potential Distributed Denial of Service attacks (DDoS). Alerts and notifications are generated, and warning notifications will be given to the source node. Upon detection of a DDoS attack, appropriate mitigation strategies are implemented to protect the network infrastructure and services. These may include traffic filtering; and rate limiting to mitigate the attack’s impact and ensure critical resource availability. The performance metrics, such as detection accuracy, false positive rate, and response time, will be measured to assess the reliability and efficiency of the solution, by developing an algorithmic model that can effectively detect and mitigate Distributed Denial of Service attacks. This chapter aims to enhance network security and ensure the uninterrupted availability of online services for digital twin environments, even in the face of evolving and sophisticated cyber threats.
