Automated brain tumor recognition using equilibrium optimizer with deep learning approach on MRI images.

Brain tumours (BT) affect human health owing to their location. Artificial intelligence (AI) is intended to assist in diagnosing and treating complex diseases by combining technologies like deep learning (DL), big data analytics, and machine learning (ML). AI can identify and categorize tumours by analyzing brain imaging approaches like Magnetic Resonance Imaging (MRI).

IoT Traffic Analyzer Tool with Automated and Holistic Feature Extraction Capability.

The Internet of Things (IoT) is an emerging technology that attracted considerable attention in the last decade to become one of the most researched topics in computer science studies. This research aims to develop a benchmark framework for a public multi-task IoT traffic analyzer tool that holistically extracts network traffic features from an IoT device in a smart home environment that researchers in various IoT industries can implement to collect information about IoT network behavior. A custom testbed with four IoT devices is created to collect real-time network traffic data based on seventeen comprehensive scenarios of these devices' possible interactions.

Detecting IoT User Behavior and Sensitive Information in Encrypted IoT-App Traffic.

Many people use smart-home devices, also known as the Internet of Things (IoT), in their daily lives. Most IoT devices come with a companion mobile application that users need to install on their smartphone or tablet to control, configure, and interface with the IoT device. IoT devices send information about their users from their app directly to the IoT manufacturer's cloud; we call this the "app-to-cloud way".