Software-defined networking (SDN) has revolutionized network management by providing modular control and data plane attributes for flexible network management. It implies the concept of separating the control and data plane attributes for flexible network management. However, centralized management due to control plane separation in SDN also exposes it to cyber threats such as Distributed Denial-of-service (DDoS) attacks that can compromise the SDN controllers. In recent research, entropy-based attack detection approaches showed much significance among other detection methods but relying on entropy itself can neglect detection in several variables such as variations in flow specification. Based on these limitations, in this work, we have designed a DDoS attack detection framework inside the SDN control plane by integrating the packet flow initiation and its specifications properties with entropy-based algorithm to ensure correct measures of attack detection. The simulation is performed on Mininet network simulator, for implementing SDN architecture and the testbed is created on UDP flood attacks on commonly used data-centric tree topologies. Based on experimentation, this lightweight framework is designed to mitigate DDoS attacks by detecting its effects in the early stages to prevent SDN controller being hijacked due to immense packet flooding Based on the results, the proposed solution assures the SDN-based DDoS attack detection and mitigation under 150 packets maintaining significantly low detection time and high accuracy.accuracy.

Therapists have used paper-based exercises to treat learning disorders for many years. Dyslexia and Dysgraphia are one of the reading and writing disorders that are common nowadays. Different serious games and interventions are developed for the improvement of dyslexic and dysgraphic children. But these games cannot engage these children for a long time. Moreover, there is a need for an assessment criterion for the performance of dyslexic and dysgraphic children. Augmented Reality is an emerging technology that is used in the educational and medical fields. Augmented Reality in learning apps increases children's performance and makes them attentive. Research shows that it has a positive impact on dyslexic children. In this case study, an augmented reality-based serious game called ARLexic Game is developed to train children with Dyslexia and Dysgraphia. Design Science Research Methodology is used to design and develop the application. An experiment is conducted with specialists in special education and children with dyslexia and Dysgraphia aged 7 to 14 years old. The outcome shows that the ARLexic Game engagement level increases with time. Children learn quickly without being bored and enjoying it.