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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–25 of 800 papers

TitleStatusHype
CyberRAG: An agentic RAG cyber attack classification and reporting tool—0
Detection of Cyber Attack in Network using Machine Learning Techniques.—0
Generative Adversarial Evasion and Out-of-Distribution Detection for UAV Cyber-Attacks—0
Poster: Enhancing GNN Robustness for Network Intrusion Detection via Agent-based Analysis—0
KnowML: Improving Generalization of ML-NIDS with Attack Knowledge Graphs—0
Robust Anomaly Detection in Network Traffic: Evaluating Machine Learning Models on CICIDS2017—0
Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT—0
On the Performance of Cyber-Biomedical Features for Intrusion Detection in Healthcare 5.0—0
A Lightweight IDS for Early APT Detection Using a Novel Feature Selection Method—0
Assessing the Resilience of Automotive Intrusion Detection Systems to Adversarial Manipulation—0
Are Trees Really Green? A Detection Approach of IoT Malware Attacks—0
Fuse and Federate: Enhancing EV Charging Station Security with Multimodal Fusion and Federated Learning—0
Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning—0
A Review of Various Datasets for Machine Learning Algorithm-Based Intrusion Detection System: Advances and Challenges—0
A Systematic Review of Metaheuristics-Based and Machine Learning-Driven Intrusion Detection Systems in IoT—0
INSIGHT: A Survey of In-Network Systems for Intelligent, High-Efficiency AI and Topology Optimization—0
Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications—0
A Robust PPO-optimized Tabular Transformer Framework for Intrusion Detection in Industrial IoT SystemsCode0
A Scalable Hierarchical Intrusion Detection System for Internet of Vehicles—0
Neuromorphic Mimicry Attacks Exploiting Brain-Inspired Computing for Covert Cyber Intrusions—0
SecCAN: An Extended CAN Controller with Embedded Intrusion DetectionCode0
Adaptive Pruning of Deep Neural Networks for Resource-Aware Embedded Intrusion Detection on the EdgeCode0
CSAGC-IDS: A Dual-Module Deep Learning Network Intrusion Detection Model for Complex and Imbalanced Data—0
A Survey of Learning-Based Intrusion Detection Systems for In-Vehicle Network—0
Adaptive Security Policy Management in Cloud Environments Using Reinforcement Learning—0
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All datasetsCICIDS2017CIC-DDoSCIC-DoSUNSW-NB15

Benchmark Results

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