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Network Intrusion Detection

Network intrusion detection is the task of monitoring network traffic to and from all devices on a network in order to detect computer attacks.

Papers

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Showing 61–70 of 261 papers

TitleStatusHype
A Combination of Temporal Sequence Learning and Data Description for Anomaly-based NIDS—0
BS-GAT Behavior Similarity Based Graph Attention Network for Network Intrusion Detection—0
Deep PackGen: A Deep Reinforcement Learning Framework for Adversarial Network Packet Generation—0
Analyzing and Storing Network Intrusion Detection Data using Bayesian Coresets: A Preliminary Study in Offline and Streaming Settings—0
A Robust Comparison of the KDDCup99 and NSL-KDD IoT Network Intrusion Detection Datasets Through Various Machine Learning Algorithms—0
Data Mining model in the discovery of trends and patterns of intruder attacks on the data network as a public-sector innovation—0
Are We There Yet? Unraveling the State-of-the-Art Graph Network Intrusion Detection Systems—0
An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection—0
A Dependable Hybrid Machine Learning Model for Network Intrusion Detection—0
Dealing with Imbalanced Classes in Bot-IoT Dataset—0
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