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 201–225 of 800 papers

TitleStatusHype
CAN-BERT do it? Controller Area Network Intrusion Detection System based on BERT Language Model—0
An Experimental Analysis of Attack Classification Using Machine Learning in IoT Networks—0
Change Detection in Noisy Dynamic Networks: A Spectral Embedding Approach—0
Characterization of Neural Networks Automatically Mapped on Automotive-grade Microcontrollers—0
Clustering Algorithm to Detect Adversaries in Federated Learning—0
CADeSH: Collaborative Anomaly Detection for Smart Homes—0
CND-IDS: Continual Novelty Detection for Intrusion Detection Systems—0
CoAP-DoS: An IoT Network Intrusion Dataset—0
ByteStack-ID: Integrated Stacked Model Leveraging Payload Byte Frequency for Grayscale Image-based Network Intrusion Detection—0
Collaborative Approaches to Enhancing Smart Vehicle Cybersecurity by AI-Driven Threat Detection—0
A new semi-supervised inductive transfer learning framework: Co-Transfer—0
Collective Anomaly Detection based on Long Short Term Memory Recurrent Neural Network—0
Adversarial Machine Learning In Network Intrusion Detection Domain: A Systematic Review—0
Conformalized density- and distance-based anomaly detection in time-series data—0
Building an Effective Intrusion Detection System using Unsupervised Feature Selection in Multi-objective Optimization Framework—0
Constrained Twin Variational Auto-Encoder for Intrusion Detection in IoT Systems—0
BS-GAT Behavior Similarity Based Graph Attention Network for Network Intrusion Detection—0
A New Intrusion Detection System using the Improved Dendritic Cell Algorithm—0
Breaking the Flow and the Bank: Stealthy Cyberattacks on Water Network Hydraulics—0
Convergence of Communications, Control, and Machine Learning for Secure and Autonomous Vehicle Navigation—0
Adversarial Machine Learning in Network Intrusion Detection Systems—0
A Content-Based Deep Intrusion Detection System—0
A cognitive based Intrusion detection system—0
C-RADAR: A Centralized Deep Learning System for Intrusion Detection in Software Defined Networks—0
AdvCat: Domain-Agnostic Robustness Assessment for Cybersecurity-Critical Applications with Categorical Inputs—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