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Advances in Electrical and Computer Engineering, 2023 In recent years, machine learning (ML) has had a significant influence on the discipline of computer security. In network security, intrusion detection systems increasingly employ machine learning techniques.
NATHANIEL, D., SOOSAI, A.
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Using CLIPS to Detect Network Intrusions [PDF]
, 2003 This paper shows how to build a network intrusion detection system by slightly modifying NASA’s CLIPS source code, introducing features such as single and multiple string pattern matching, certainty factors and time-stamp operators. Several Snort functions and plugins were adapted and used for packet decoding and preprocessing to provide the basic ...
Alípio, Pedro +2 more
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网络与信息安全学报, 2018 Existing intrusion detection models generally only analyze the static characteristics of network intrusion actions,resulting in low detection rate and high false positive rate,and cannot effectively detect low-frequency attacks.Therefore,a novel ...
Binghao YAN,Guodong HAN
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A consensus based network intrusion detection system
, 2015 Network intrusion detection is the process of identifying malicious behaviors that target a network and its resources. Current systems implementing intrusion detection processes observe traffic at several data collecting points in the network but ...
Curtis, Philip +2 more
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An intrusion detection algorithm for sensor network based on normalized cut spectral clustering.
PLoS ONE, 2019 Sensor network intrusion detection has attracted extensive attention. However, previous intrusion detection methods face the highly imbalanced attack class distribution problem, and they may not achieve a satisfactory performance.
Gaoming Yang +4 more
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Intrusion Detection Over Encrypted Network Data
The Computer Journal, 2019 Abstract Effective protection against cyber-attacks requires constant monitoring and analysis of system data in an IT infrastructure, such as log files and network packets, which may contain private and sensitive information. Security operation centers (SOC), which are established to detect, analyze and respond to cyber-security ...
Karaçay, Leyli +2 more
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Operational Network Intrusion Detection [PDF]
, 2008 The goal of this thesis is to examine dependencies and tradeoffs between the resource usage (CPU and memory) and the analysis capabilities of Network Intrusion Detection Systems (NIDS). We base our work on the experience of running NIDS in large network environments (among them the Münchener Wissenschaftsnetz (MWN)). These show that resource management
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Majlesi Journal of Electrical Engineering, 2023 In recent decades, network security has become increasingly crucial, and intrusion detection systems play a critical role in securing it. An intrusion Detection System (IDS) is a mechanism that protects the network from various possible intrusions by ...
Seshu Bhavani Mallampati, Seetha Hari
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Intrusion Detection for IoT Based on Improved Genetic Algorithm and Deep Belief Network
IEEE Access, 2019 With the advent of the Internet of Things (IoT), the security of the network layer in the IoT is getting more and more attention. The traditional intrusion detection technologies cannot be well adapted in the complex Internet environment of IoT.
Ying Zhang, Peisong Li, Xinheng Wang
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Deep Learning-Based Network Intrusion Detection Using Multiple Image Transformers
Applied Sciences, 2023 The development of computer vision-based deep learning models for accurate two-dimensional (2D) image classification has enabled us to surpass existing machine learning-based classifiers and human classification capabilities.
Taehoon Kim, Wooguil Pak
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