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 491500 of 800 papers

TitleStatusHype
Segmented Federated Learning for Adaptive Intrusion Detection System0
Precise Feature Selection and Case Study of Intrusion Detection in an Industrial Control System (ICS) Environment0
Feature selection for intrusion detection systems0
Federated Learning for Intrusion Detection in IoT Security: A Hybrid Ensemble Approach0
DeepAuditor: Distributed Online Intrusion Detection System for IoT devices via Power Side-channel Auditing0
Zero-shot learning approach to adaptive Cybersecurity using Explainable AI0
Artificial Neural Network for Cybersecurity: A Comprehensive Review0
Intrusion Detection and Localization for Networked Embedded Control Systems0
Detecting message modification attacks on the CAN bus with Temporal Convolutional NetworksCode0
Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions0
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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