Tag: software-defined networking

Computer scientists have developed a hybrid detection system that couples Shannon entropy with Kullback–Leibler divergence to identify network flooding attacks ...

A systematic survey published in Discover Networks details how decentralized federated learning secures sensitive Internet of Things data against poisoning ...

A systematic review of 110 studies reveals that machine learning strengthens campus defenses against distributed denial of service and address ...

Researchers have developed a reinforcement learning framework that autonomously diagnoses and remediates multiple SDN fault types within tens of seconds.

A new study presents HPQ-EAI-IDS, a unified intrusion detection system for IoT networks that combines explainable AI, post-quantum security, and ...

Researchers have combined software-defined networking, a self-mutable blockchain and post-quantum cryptography into a simulated framework designed to secure Internet of ...

A new review of 29 recent studies finds that no deep learning intrusion detection system has been evaluated jointly for ...

Researchers have applied a krill herd optimization algorithm to software-defined network clustering, reporting significant gains in latency, cluster separation, and ...

Researchers have built a federated, explainable VAE-LSTM framework that detects previously unseen DDoS attacks in software-defined healthcare networks with over ...

Researchers have developed an AI-driven trust and decision-making framework that uses software-defined networking and the Bat Algorithm to select secure, ...