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Deep Convolutional Neural Network for Active Intrusion Detection and Protect data from Passive Intrusion by Pascal Triangle
Active and passive intrusion are the two types of intrusion. The active intrusion attempts to modify the data and the passive intrusion observes the...
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Advancing IoT security: a comprehensive AI-based trust framework for intrusion detection
Over the years, the Internet of Things (IoT) devices have shown rapid proliferation and development in various domains. However, the widespread...
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Feature Extraction and Anomaly Detection Using Different Autoencoders for Modeling Intrusion Detection Systems
Maintaining network security by preventing attacks is essential for a network intrusion detection system. Machine learning techniques heavily depend...
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A novel transfer extreme learning machine from multiple sources for intrusion detection
Intrusion detection systems (IDS), as a technology to protect networks from attacks, play a pivotal role in ensuring computer system and network...
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Network Intrusion Detection Based on Explainable Artificial Intelligence
People often use similar methods to invade network traffic, such as flood attacks and Ddos attacks. Early detection of malicious traffic usually uses...
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Meta learning-based few-shot intrusion detection for 5G-enabled industrial internet
With the formation and popularization of the 5G-enabled industrial internet, cybersecurity risks are increasing, and the limited number of attack...
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Intrusion Detection System Using Machine Learning
In recent years, the field of network security has witnessed severe advances in the development of intrusion detection systems to protect computer...
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Providing a hybrid approach to increase the accuracy of intrusion detection systems in computer networks
Intrusion detection is a critical obstacle in the realm of security and data mining methodologies. Consequently, researchers have extensively...
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Blockchain-Enabled Lightweight Intrusion Detection System for Secure MANETs
In this study, we provide a novel method dubbed BL-IDS, which makes use of a decentralized Blockchain network to power a minimal intrusion detection...
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Self-healing hybrid intrusion detection system: an ensemble machine learning approach
The increasing complexity and adversity of cyber-attacks have prompted discussions in the cyber scenario for a prognosticate approach, rather than a...
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Enhancing intrusion detection recursive feature elimination with resampling in WSN
With the proliferation of technologies such as the Internet of Things, Cloud computing, and Social Networking, large quantities of network traffic...
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LSF-IDM: Deep learning-based lightweight semantic fusion intrusion detection model for automotive
Controller Area Network (CAN) is increasing connectivity to the external environment for intelligent interconnection in autonomous vehicles, as well...
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A novel intrusion detection system for internet of things devices and data
As we enter the new age of the Internet of Things (IoT) and wearable gadgets, sensors, and embedded devices are extensively used for data aggregation...
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An adversarial environment reinforcement learning-driven intrusion detection algorithm for Internet of Things
The increasing prevalence of Internet of Things (IoT) systems has made them attractive targets for malicious actors. To address the evolving threats...
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A network intrusion detection framework on sparse deep denoising auto-encoder for dimensionality reduction
In today's internet-driven world, a multitude of attacks occurs daily, propelled by a vast user base. The effective detection of these numerous...
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A Robust SNMP-MIB Intrusion Detection System Against Adversarial Attacks
With the increase in cyber security attacks, organizations tend to use an intrusion detection system (IDS) based on machine learning. Through the...
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Intelligent fuzzy logic based intrusion detection system for effective detection of black hole attack in WSN
A wireless sensor network (WSN) is a distributed collection of tiny, low-power, wireless devices which are deployed in a physical environment to...
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Machine learning based intrusion detection system for IoMT
Millennials have the advantage of accessing readily available modern scientific advancements, particularly in technology. One of these technologies...
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Intrusion Detection Method Based on Denoising Diffusion Probabilistic Models for UAV Networks
Security is important for UAV networks because of the need for a cyber-secure flying air space for UAV group communication to complete the complex...
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Pre-trained language model-enhanced conditional generative adversarial networks for intrusion detection
As cyber threats continue to evolve, ensuring network security has become increasingly critical. Deep learning-based intrusion detection systems...
