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 391400 of 800 papers

TitleStatusHype
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System0
AI-based Two-Stage Intrusion Detection for Software Defined IoT Networks0
AIDPS:Adaptive Intrusion Detection and Prevention System for Underwater Acoustic Sensor Networks0
AI-Driven Chatbot for Intrusion Detection in Edge Networks: Enhancing Cybersecurity with Ethical User Consent0
AI-Driven Intrusion Detection Systems (IDS) on the ROAD Dataset: A Comparative Analysis for Automotive Controller Area Network (CAN)0
A Life-long Learning Intrusion Detection System for 6G-Enabled IoV0
A Lightweight FPGA-based IDS-ECU Architecture for Automotive CAN0
A Lightweight IDS for Early APT Detection Using a Novel Feature Selection Method0
A Lightweight Multi-Attack CAN Intrusion Detection System on Hybrid FPGAs0
A Machine Learning based Empirical Evaluation of Cyber Threat Actors High Level Attack Patterns over Low level Attack Patterns in Attributing Attacks0
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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