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Deep Stacking Network for Intrusion Detection [PDF]
Preventing network intrusion is the essential requirement of network security. In recent years, people have conducted a lot of research on network intrusion detection systems.
Yifan Tang, Lize Gu, Leiting Wang
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Oblivious network intrusion detection systems. [PDF]
Abstract A main function of network intrusion detection systems (NIDSs) is to monitor network traffic and match it against rules. Oblivious NIDSs (O-NIDS) perform the same tasks of NIDSs but they use encrypted rules and produce encrypted results without being able to decrypt the rules or the results.
Sayed MA, Taha M.
europepmc +4 more sources
ADFCNN-BiLSTM: A Deep Neural Network Based on Attention and Deformable Convolution for Network Intrusion Detection [PDF]
Network intrusion detection systems can identify intrusion behavior in a network by analyzing network traffic data. It is challenging to detect a very small proportion of intrusion data from massive network traffic and identify the attack class in ...
Bin Li, Jie Li, Mingyu Jia
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Wireless Network Intrusion Detection Based on Improved Convolutional Neural Network
The diversification of wireless network traffic attack characteristics has led to the problems what traditional intrusion detection technology with high false positive rate, low detection efficiency, and poor generalization ability.
Hongyu Yang, Fengyan Wang
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Wireless Network Intrusion Detection Algorithm Based on Multiple Perspectives Hierarchical Clustering [PDF]
Aiming at the problems of high false detection rate, difficult to find unknown attack behavior and high cost of obtaining marked data in existing wireless network intrusion detection algorithms based on supervised learning, this paper proposes an ...
DONG Xinyu, XIE Bin, ZHAO Xusheng, GAO Xinbao
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Intrusion Detection Method Based on Denoising Autoencoder and Three-way Decisions [PDF]
Intrusion detection plays a vital role in computer network security.Intrusion detection is one of the key technologies of network security and needs to be kept under constant attention.As the network environment becomes more and more complex,network ...
ZHANG Shi-peng, LI Yong-zhong
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Network intrusion detection is an important technology in national cyberspace security strategy and has become a research hotspot in various cyberspace security issues in recent years.
Li Zou +4 more
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Analysis of Autoencoders for Network Intrusion Detection [PDF]
As network attacks are constantly and dramatically evolving, demonstrating new patterns, intelligent Network Intrusion Detection Systems (NIDS), using deep-learning techniques, have been actively studied to tackle these problems. Recently, various autoencoders have been used for NIDS in order to accurately and promptly detect unknown types of attacks ...
Youngrok Song +2 more
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HDLNIDS: Hybrid Deep-Learning-Based Network Intrusion Detection System
Attacks on networks are currently the most pressing issue confronting modern society. Network risks affect all networks, from small to large. An intrusion detection system must be present for detecting and mitigating hostile attacks inside networks ...
Emad Ul Haq Qazi +2 more
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Few-Shot network intrusion detection based on prototypical capsule network with attention mechanism
Network intrusion detection plays a crucial role in ensuring network security by distinguishing malicious attacks from normal network traffic. However, imbalanced data affects the performance of intrusion detection system.
Handi Sun +3 more
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