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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 1–10 of 800 papers

Title	Date	Tasks	Status	Hype	Score
A Transfer Learning and Optimized CNN Based Intrusion Detection System for Internet of Vehicles	Jan 27, 2022	Autonomous VehiclesCyber Attack Detection	CodeCode Available	2	5
LCCDE: A Decision-Based Ensemble Framework for Intrusion Detection in The Internet of Vehicles	Aug 5, 2022	Autonomous VehiclesIntrusion Detection	CodeCode Available	2	5
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection	Jun 30, 2022	Intrusion DetectionNetwork Intrusion Detection	CodeCode Available	1	5
An Intrusion Detection System based on Deep Belief Networks	Jul 5, 2022	Intrusion DetectionNetwork Intrusion Detection	CodeCode Available	1	5
A flow-based IDS using Machine Learning in eBPF	Feb 19, 2021	BIG-bench Machine LearningIntrusion Detection	CodeCode Available	1	5
AnomalyDAE: Dual autoencoder for anomaly detection on attributed networks	Feb 10, 2020	Anomaly DetectionAttribute	CodeCode Available	1	5
3D-IDS: Doubly Disentangled Dynamic Intrusion Detection	Jul 2, 2023	DisentanglementFew-Shot Learning	CodeCode Available	1	5
A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic Classification	Feb 11, 2022	Intrusion DetectionTraffic Classification	CodeCode Available	1	5
Adaptive Intrusion Detection in the Networking of Large-Scale LANs with Segmented Federated Learning	Dec 16, 2020	Federated LearningIntrusion Detection	CodeCode Available	1	5
A new Deep Learning Based Intrusion Detection System for Cloud Security	Jun 13, 2021	Cloud ComputingDeep Learning	CodeCode Available	1	5

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All datasets CICIDS2017 CIC-DDoS CIC-DoS UNSW-NB15

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Random Forest	Accuracy (%)	98.13	—	Unverified
2	K-Nearest Neighbors	Accuracy (%)	98.07	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MSTREAM-PCA	AUC	0.94	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MSTREAM-IB	AUC	0.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MSTREAM-AE	AUC	0.9	—	Unverified