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 361370 of 800 papers

TitleStatusHype
Training Automated Defense Strategies Using Graph-based Cyber Attack Simulations0
Late Breaking Results: Scalable and Efficient Hyperdimensional Computing for Network Intrusion Detection0
BS-GAT Behavior Similarity Based Graph Attention Network for Network Intrusion Detection0
Explainable Intrusion Detection Systems Using Competitive Learning Techniques0
FeDiSa: A Semi-asynchronous Federated Learning Framework for Power System Fault and Cyberattack Discrimination0
Adaptive Bi-Recommendation and Self-Improving Network for Heterogeneous Domain Adaptation-Assisted IoT Intrusion Detection0
Feature Reduction Method Comparison Towards Explainability and Efficiency in Cybersecurity Intrusion Detection Systems0
A Novel Multi-Stage Approach for Hierarchical Intrusion DetectionCode0
Review on the Feasibility of Adversarial Evasion Attacks and Defenses for Network Intrusion Detection Systems0
Adv-Bot: Realistic Adversarial Botnet Attacks against Network Intrusion Detection Systems0
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Benchmark Results

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