SOTAVerified

Intrusion Detection

Intrusion Detection is the process of dynamically monitoring events occurring in a computer system or network, analyzing them for signs of possible incidents and often interdicting the unauthorized access. This is typically accomplished by automatically collecting information from a variety of systems and network sources, and then analyzing the information for possible security problems.

Source: Machine Learning Techniques for Intrusion Detection

Papers

Showing 201210 of 800 papers

TitleStatusHype
BS-GAT Behavior Similarity Based Graph Attention Network for Network Intrusion Detection0
A New Intrusion Detection System using the Improved Dendritic Cell Algorithm0
Change Detection in Noisy Dynamic Networks: A Spectral Embedding Approach0
Characterization of Neural Networks Automatically Mapped on Automotive-grade Microcontrollers0
Clustering Algorithm to Detect Adversaries in Federated Learning0
Breaking the Flow and the Bank: Stealthy Cyberattacks on Water Network Hydraulics0
CND-IDS: Continual Novelty Detection for Intrusion Detection Systems0
CoAP-DoS: An IoT Network Intrusion Dataset0
Adversarial Machine Learning in Network Intrusion Detection Systems0
A Content-Based Deep Intrusion Detection System0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Random ForestAccuracy (%)98.13Unverified
2K-Nearest NeighborsAccuracy (%)98.07Unverified
#ModelMetricClaimedVerifiedStatus
1MSTREAM-PCAAUC0.94Unverified
#ModelMetricClaimedVerifiedStatus
1MSTREAM-IBAUC0.95Unverified
#ModelMetricClaimedVerifiedStatus
1MSTREAM-AEAUC0.9Unverified