Network security is a critical concern in the development of interconnected and shared networks, given their vulnerability to various attacks. Intrusion detection technology has emerged as a crucial defense mechanism against malicious activities. Traditional methods face limitations in detecting complex intrusion behaviors, leading to a shift towards machine learning-based approaches. Deep learning models like Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory Neural Networks (BiLSTM) offer promising solutions by capturing intricate patterns in network traffic data. This paper introduces a fusion network intrusion detection model, leveraging Grey Wolf Optimizer (GWO) and Convolutional Neural Network-Bidirectional Long Short-Term Memory (CNN-BiLSTM), addressing emerging challenges in network security. The model's efficacy was assessed on the CICIDS2017 dataset and compared against Random Forest and CNN-BiLSTM models. Results confirm the viability and efficacy of the proposed approach, offering a novel strategy for network intrusion detection.
KEYWORDS: Computer security, Network security, Video, Data acquisition, Video surveillance, Sensors, Internet of things, Design, Data transmission, Cameras
To address the challenges of wiring operation and maintenance in substations and the security issues associated with wireless data acquisition in smart grid environments, we have developed a secure wireless data acquisition system for substation monitoring. This system integrates 5G, short-range wireless communication, Internet of Things (IoT) technology, and video processing to establish a secure and unified access model. The system comprises an intelligent gateway deployed at the wireless network boundary, equipped with hardware encryption cards for terminal authentication, data encryption, and information security. The gateway seamlessly integrates with the IoT system architecture, encompassing perception, edge computing, transport, and service layers. A security access module for the terminal is introduced in the design, taking into account the security constraints in the substation environment. This module ensures encrypted data transmission between the gateway and the terminal, providing a secure access solution for video and sensors.
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