Results 11 to 20 of about 27,263 (310)
HDLNIDS: Hybrid Deep-Learning-Based Network Intrusion Detection System
Applied Sciences, 2023 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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Network Intrusion Detection [PDF]
, 2011 Attacks against computers and the Internet are in the news every week. These primarily take the form of malicious code such as viruses and worms, or denial of service attacks. Less commonly reported are attacks which gain access to computers, either for the purpose of producing damage (such as defacing web sites or deleting data) or for the ...
Yong Shi +4 more
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Acta Infologica, 2023 The threat of network intrusion has become much more severe due to the increasing network flow. Therefore, network intrusion detection is one of the most concerned areas of network security.
Ahmet Okan Arık +1 more
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Towards an effective deep learning-based intrusion detection system in the internet of things
Telematics and Informatics Reports, 2022 Distributed Sensor Networks play a vital role in the day-to-day world of computing applications, from the cloud to the Internet of Things (IoT). These computing applications devices are normally attached with the microcontrollers like Sensors, actuators,
Pampapathi B M +2 more
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CNID: Research of Network Intrusion Detection Based on Convolutional Neural Network
Discrete Dynamics in Nature and Society, 2020 Network intrusion detection system can effectively detect network attack behaviour, which is very important to network security. In this paper, a multiclassification network intrusion detection model based on convolutional neural network is proposed, and
Guojie Liu, Jianbiao Zhang
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IEEE Access, 2020 In this paper, an intrusion detection system is introduced that uses data mining and machine learning concepts to detect network intrusion patterns. In the proposed method, an artificial neural network (ANN) is used as a learning technique in intrusion ...
Shadi Moghanian +3 more
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A Bagging Strategy-Based Kernel Extreme Learning Machine for Complex Network Intrusion Detection [PDF]
EAI Endorsed Transactions on Scalable Information Systems, 2021 Network intrusion can enter the network through informal channels. Some illegal users utilize Trojans and self-programmed attack to change the network security system, so that the system loses the defense and alarm function and the Hacker ...
Shoulin Yin +4 more
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Intrusion Detection in SCADA Networks [PDF]
, 2010 Supervisory Control and Data Acquisition (SCADA) systems are a critical part of large industrial facilities, such as water distribution infrastructures. With the goal of reducing costs and increasing efficiency, these systems are becoming increasingly interconnected. However, this has also exposed them to a wide range of network security problems.
Barbosa, Rafael Ramos Regis, Pras, Aiko
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Remote Sensing, 2023 With the rapid development of the Internet of Things (IoT)-based near-Earth remote sensing technology, the problem of network intrusion for near-Earth remote sensing systems has become more complex and large-scale.
Yalu Wang +6 more
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Enhanced Network Intrusion Detection System [PDF]
Sensors, 2021 A reasonably good network intrusion detection system generally requires a high detection rate and a low false alarm rate in order to predict anomalies more accurately. Older datasets cannot capture the schema of a set of modern attacks; therefore, modelling based on these datasets lacked sufficient generalizability. This paper operates on the UNSW-NB15
Ketan Kotecha +8 more
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