[PDF][PDF] 网络入侵检测技术综述
蹇诗婕， 卢志刚， 杜丹， 姜波， 刘宝旭 - 信息安全学报, 2020 - jcs.iie.ac.cn
摘要随着互联网时代的发展, 内部威胁, 零日漏洞和DoS 攻击等攻击行为日益增加,
网络安全变得越来越重要, 入侵检测已成为网络攻击检测的一种重要手段. 随着机器学习算法的 …
网络安全变得越来越重要, 入侵检测已成为网络攻击检测的一种重要手段. 随着机器学习算法的 …
Building an efficient intrusion detection system based on feature selection and ensemble classifier
Y Zhou, G Cheng, S Jiang, M Dai - Computer networks, 2020 - Elsevier
Intrusion detection system (IDS) is one of extensively used techniques in a network topology
to safeguard the integrity and availability of sensitive assets in the protected systems …
to safeguard the integrity and availability of sensitive assets in the protected systems …
A feature selection algorithm for intrusion detection system based on pigeon inspired optimizer
Feature selection plays a vital role in building machine learning models. Irrelevant features
in data affect the accuracy of the model and increase the training time needed to build the …
in data affect the accuracy of the model and increase the training time needed to build the …
Improved discrete salp swarm algorithm using exploration and exploitation techniques for feature selection in intrusion detection systems
M Barhoush, BH Abed-alguni… - The Journal of …, 2023 - Springer
The salp swarm algorithm (SSA) is a well-known optimization algorithm that is increasingly
being utilized to solve many sorts of optimization problems. However, SSA may converge to …
being utilized to solve many sorts of optimization problems. However, SSA may converge to …
Enhancing network intrusion detection using an ensemble voting classifier for internet of things
In the context of 6G technology, the Internet of Everything aims to create a vast network that
connects both humans and devices across multiple dimensions. The integration of smart …
connects both humans and devices across multiple dimensions. The integration of smart …
Grey wolf based feature reduction for intrusion detection in WSN using LSTM
S Karthic, S Manoj Kumar… - International Journal of …, 2022 - Springer
In the recent days all the digital devices including devices used in Healthcare, Personal
Digital Assistance etc. are connected to the network, consequently data is exposed to …
Digital Assistance etc. are connected to the network, consequently data is exposed to …
Numerical feature selection and hyperbolic tangent feature scaling in machine learning-based detection of anomalies in the computer network behavior
Anomaly-based intrusion detection systems identify the computer network behavior which
deviates from the statistical model of typical network behavior. Binary classifiers based on …
deviates from the statistical model of typical network behavior. Binary classifiers based on …
A binary firefly algorithm based feature selection method on high dimensional intrusion detection data
YK Saheed - Illumination of artificial intelligence in cybersecurity and …, 2022 - Springer
Network intrusion detection system are significant features that contribute to the enterprises
and organization network success. In the past decade, Intrusion Detection system (IDS) …
and organization network success. In the past decade, Intrusion Detection system (IDS) …
[HTML][HTML] Intrusion detection technique based on flow aggregation and latent semantic analysis
J Wu, W Wang, L Huang, F Zhang - Applied Soft Computing, 2022 - Elsevier
Traditional network intrusion detection systems cannot identify new burgeoning invasive
activities due to the inconspicuous features of malicious behaviors and the enormous …
activities due to the inconspicuous features of malicious behaviors and the enormous …
Cybersecurity in smart cities: Detection of opposing decisions on anomalies in the computer network behavior
The increased use of urban technologies in smart cities brings new challenges and issues.
Cyber security has become increasingly important as many critical components of …
Cyber security has become increasingly important as many critical components of …