Intrusion Detection

Intrusion detection focuses on automatically identifying malicious activities within computer networks and systems, aiming to enhance cybersecurity. Current research emphasizes the application of machine learning, particularly deep learning models like transformers, recurrent neural networks (RNNs), and graph neural networks (GNNs), often combined with ensemble methods and autoencoders for feature extraction and improved accuracy. This field is crucial for protecting diverse systems, from IoT devices and 5G networks to autonomous vehicles and industrial control systems, and advancements in intrusion detection directly impact the security and reliability of critical infrastructure and everyday technologies.

Papers

February 3, 2023

IoT Botnet Detection Using an Economic Deep Learning Model
Nelly Elsayed, Zag ElSayed, Magdy Bayoumi
Internet of Thing Intrusion Detection Security Challenge

December 26, 2022

Investigation and rectification of NIDS datasets and standardized feature set derivation for network attack detection with graph neural networks
Anton Raskovalov, Nikita Gabdullin, Vasily Dolmatov
Neural Network Graph Drawing Internet of Thing Intrusion Detection Network Intrusion Detection Network Intrusion Detection System

December 2, 2022

A Hybrid Deep Learning Anomaly Detection Framework for Intrusion Detection
Rahul Kale, Zhi Lu, Kar Wai Fok, Vrizlynn L. L. Thing
Anomaly Detection Unsupervised Anomaly Detection Intrusion Detection Deep Learning Based Anomaly Detection

November 18, 2022

Intrusion Detection in Internet of Things using Convolutional Neural Networks
Martin Kodys, Zhi Lu, Kar Wai Fok, Vrizlynn L. L. Thing
Deep Learning Convolutional Neural Network LSTM Network Internet of Thing Intrusion Detection Intrusion Detection System Internet of Thing Device Good Thing

October 6, 2022

September 12, 2022

Intrusion Detection Systems Using Support Vector Machines on the KDDCUP'99 and NSL-KDD Datasets: A Comprehensive Survey
Mikel K. Ngueajio, Gloria Washington, Danda B. Rawat, Yolande Ngueabou
Comprehensive Survey Intrusion Detection Intrusion Detection System KDD Cup NSL KDD

August 25, 2022

A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using wireless sensor networks
Abhilash Singh, J. Amutha, Jaiprakash Nagar, Sandeep Sharma
Data Detection Deep Learning Approach Intrusion Detection Knowledge Barrier Sensor Network Sensor Placement Packing Circle

August 22, 2022

ECU Identification using Neural Network Classification and Hyperparameter Tuning
Kunaal Verma, Mansi Girdhar, Azeem Hafeez, Selim S. Awad
Intrusion Detection Spectral Feature Hyperparameter Tuning Controller Area Network Neural Classifier Fingerprint Intrusion Detection System Traditional ECU

August 16, 2022

Designing an Artificial Immune System inspired Intrusion Detection System
William Anderson, Kaneesha Moore, Jesse Ables, Sudip Mittal, Shahram Rahimi, Ioana Banicescu, Maria Seale
Intrusion Detection Intrusion Detection System Artificial Immune System

August 5, 2022

LCCDE: A Decision-Based Ensemble Framework for Intrusion Detection in The Internet of Vehicles
Li Yang, Abdallah Shami, Gary Stevens, Stephen De Rusett
Intrusion Detection Vehicle Plan Intrusion Detection System Internet of Vehicle Learning Based Intrusion Detection Voting Ensemble

July 20, 2022

Digital Twin-based Intrusion Detection for Industrial Control Systems
Seba Anna Varghese, Alireza Dehlaghi Ghadim, Ali Balador, Zahra Alimadadi, Panos Papadimitratos
Intrusion Detection Industrial Control

July 19, 2022

IDPS Signature Classification with a Reject Option and the Incorporation of Expert Knowledge
Hidetoshi Kawaguchi, Yuichi Nakatani, Shogo Okada
Expert Knowledge Intrusion Detection Signature Analysis Signature Transform Reject Option

July 18, 2022

Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications
Ali Raza, Shujun Li, Kim-Phuc Tran, Ludovic Koehl
Adversarial Attack Anomaly Detection Poisoning Attack Intrusion Detection Data Poisoning Attack Federated Learning Application

July 7, 2022

Bayesian Hyperparameter Optimization for Deep Neural Network-Based Network Intrusion Detection
Mohammad Masum, Hossain Shahriar, Hisham Haddad, Md Jobair Hossain Faruk, Maria Valero, Md Abdullah Khan, Mohammad A. Rahman, Muhaiminul I. Adnan, Alfredo Cuzzocrea
Intrusion Detection Network Intrusion Detection Deeper Network

June 25, 2022

Robustness Evaluation of Deep Unsupervised Learning Algorithms for Intrusion Detection Systems
D'Jeff Kanda Nkashama, Arian Soltani, Jean-Charles Verdier, Marc Frappier, Pierre-Martin Tardif, Froduald Kabanza
Intrusion Detection Intrusion Detection System Robustness Evaluation Data Poisoning Data Contamination Unsupervised Deep Learning Based Intrusion Detection

June 21, 2022

June 16, 2022

When a RF Beats a CNN and GRU, Together -- A Comparison of Deep Learning and Classical Machine Learning Approaches for Encrypted Malware Traffic Classification
Adi Lichy, Ofek Bader, Ran Dubin, Amit Dvir, Chen Hajaj
Deep Learning CNN Network Intrusion Detection Traffic Classification Malware Family Classical Machine Learning Novel RF Editing Pipeline Malicious Traffic Encrypted Traffic Classification

May 29, 2022

Learning Security Strategies through Game Play and Optimal Stopping
Kim Hammar, Rolf Stadler
Reinforcement Learning Intrusion Detection Self Play Defense Algorithm Game Play

Intrusion Detection

Papers

IoT Botnet Detection Using an Economic Deep Learning Model

Investigation and rectification of NIDS datasets and standardized feature set derivation for network attack detection with graph neural networks

A Hybrid Deep Learning Anomaly Detection Framework for Intrusion Detection

Intrusion Detection in Internet of Things using Convolutional Neural Networks

LGTBIDS: Layer-wise Graph Theory Based Intrusion Detection System in Beyond 5G

Effective Metaheuristic Based Classifiers for Multiclass Intrusion Detection

Intrusion Detection Systems Using Support Vector Machines on the KDDCUP'99 and NSL-KDD Datasets: A Comprehensive Survey

A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using wireless sensor networks

ECU Identification using Neural Network Classification and Hyperparameter Tuning

Designing an Artificial Immune System inspired Intrusion Detection System

LCCDE: A Decision-Based Ensemble Framework for Intrusion Detection in The Internet of Vehicles

Digital Twin-based Intrusion Detection for Industrial Control Systems

IDPS Signature Classification with a Reject Option and the Incorporation of Expert Knowledge

Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications

Bayesian Hyperparameter Optimization for Deep Neural Network-Based Network Intrusion Detection

Robustness Evaluation of Deep Unsupervised Learning Algorithms for Intrusion Detection Systems

Using EBGAN for Anomaly Intrusion Detection

Open-Source Framework for Encrypted Internet and Malicious Traffic Classification

When a RF Beats a CNN and GRU, Together -- A Comparison of Deep Learning and Classical Machine Learning Approaches for Encrypted Malware Traffic Classification

Learning Security Strategies through Game Play and Optimal Stopping