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 376–400 of 800 papers

TitleStatusHype
Behavioural Reports of Multi-Stage MalwareCode0
Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification—0
Leveraging Planning Landmarks for Hybrid Online Goal Recognition—0
Heterogeneous Domain Adaptation for IoT Intrusion Detection: A Geometric Graph Alignment Approach—0
BayBFed: Bayesian Backdoor Defense for Federated Learning—0
Novelty Detection in Network Traffic: Using Survival Analysis for Feature Identification—0
DRL-GAN: A Hybrid Approach for Binary and Multiclass Network Intrusion Detection—0
Detection, Explanation and Filtering of Cyber Attacks Combining Symbolic and Sub-Symbolic Methods—0
Ensemble learning techniques for intrusion detection system in the context of cybersecurity—0
DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection—0
Synthesis of Adversarial DDOS Attacks Using Tabular Generative Adversarial NetworksCode0
AdvCat: Domain-Agnostic Robustness Assessment for Cybersecurity-Critical Applications with Categorical Inputs—0
Separating Flows in Encrypted Tunnel TrafficCode0
A Dependable Hybrid Machine Learning Model for Network Intrusion Detection—0
Application of a Dynamic Line Graph Neural Network for Intrusion Detection With Semisupervised Learning—0
A Hybrid Deep Learning Anomaly Detection Framework for Intrusion Detection—0
Network Security Modelling with Distributional Data—0
Intrusion Detection in Internet of Things using Convolutional Neural Networks—0
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System—0
Reliable Malware Analysis and Detection using Topology Data AnalysisCode0
Joint Semantic Transfer Network for IoT Intrusion Detection—0
GowFed -- A novel Federated Network Intrusion Detection System—0
TAD: Transfer Learning-based Multi-Adversarial Detection of Evasion Attacks against Network Intrusion Detection Systems—0
CAN-BERT do it? Controller Area Network Intrusion Detection System based on BERT Language Model—0
DI-NIDS: Domain Invariant Network Intrusion Detection System—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