Intrusion Detection System

Intrusion Detection Systems (IDS) aim to identify malicious activities within computer networks, primarily by analyzing network traffic patterns to distinguish between normal and anomalous behavior. Current research emphasizes improving IDS accuracy and reliability through advanced machine learning techniques, including deep learning models like convolutional neural networks (CNNs), recurrent neural networks (RNNs, such as LSTMs), and graph neural networks (GNNs), as well as ensemble methods and federated learning for enhanced privacy and scalability. The development of more robust, explainable, and efficient IDSs is crucial for securing increasingly complex and interconnected systems, impacting both cybersecurity practices and the broader field of machine learning.

Papers

January 16, 2023

Novelty Detection in Network Traffic: Using Survival Analysis for Feature Identification
Taylor Bradley, Elie Alhajjar, Nathaniel Bastian
Intrusion Detection System Novelty Detection Network Traffic Network Intrusion Unknown Attack

January 5, 2023

DRL-GAN: A Hybrid Approach for Binary and Multiclass Network Intrusion Detection
Caroline Strickland, Chandrika Saha, Muhammad Zakar, Sareh Nejad, Noshin Tasnim, Daniel Lizotte, Anwar Haque
Generative Adversarial Network Intrusion Detection System Hybrid Approach Binary Code Multi Class Anomaly Detection Advanced Persistent Threat

December 21, 2022

Ensemble learning techniques for intrusion detection system in the context of cybersecurity
Andricson Abeline Moreira, Carlos A. C. Tojeiro, Carlos J. Reis, Gustavo Henrique Massaro, Igor Andrade Brito e Kelton A. P. da Costa
Context Information Ensemble Learning Diverse Ensemble Support Vector Machine Barzilai Borwein Technique Intrusion Detection System Cybersecurity Perspective Distributed Denial of Service

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 12, 2022

Anomaly Detection via Federated Learning
Marc Vucovich, Amogh Tarcar, Penjo Rebelo, Narendra Gade, Ruchi Porwal, Abdul Rahman, Christopher Redino, Kevin Choi, Dhruv Nandakumar, Robert Schiller, Edward Bowen, Alex West, Sanmitra Bhattacharya, Balaji Veeramani
Anomaly Detection Intrusion Detection System

October 6, 2022

September 29, 2022

FastPacket: Towards Pre-trained Packets Embedding based on FastText for next-generation NIDS
Khloud Al Jallad
Deep Learning Pre Training Intrusion Detection System Pre Training Task Novel Attack Based NIDS

September 28, 2022

Anomaly detection optimization using big data and deep learning to reduce false-positive
Khloud Al Jallad, Mohamad Aljnidi, Mohammad Said Desouki
Deep Learning Big Data Intrusion Detection System Based Intrusion Detection

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

September 5, 2022

RX-ADS: Interpretable Anomaly Detection using Adversarial ML for Electric Vehicle CAN data
Chathurika S. Wickramasinghe, Daniel L. Marino, Harindra S. Mavikumbure, Victor Cobilean, Timothy D. Pennington, Benny J. Varghese, Craig Rieger, Milos Manic
Anomaly Detection Adversarial Learning Intrusion Detection System Electric Vehicle Car Hacking Dataset

August 20, 2022

Improving Multilayer-Perceptron(MLP)-based Network Anomaly Detection with Birch Clustering on CICIDS-2017 Dataset
Yuhua Yin, Julian Jang-Jaccard, Fariza Sabrina, Jin Kwak
Intrusion Detection System Hierarchical Clustering Unsupervised Clustering Multi Class Anomaly Detection Cse Cic Ids2018

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 18, 2022

Supervised Contrastive ResNet and Transfer Learning for the In-vehicle Intrusion Detection System
Thien-Nu Hoang, Daehee Kim
Contrastive Learning Transfer Learning Intrusion Detection System ResNet Model Controller Area Network Car Hacking Dataset

July 15, 2022

Creating an Explainable Intrusion Detection System Using Self Organizing Maps
Jesse Ables, Thomas Kirby, William Anderson, Sudip Mittal, Shahram Rahimi, Ioana Banicescu, Maria Seale
Explainable Artificial Intelligence Intrusion Detection System Self Organizing Map

July 13, 2022

Explainable Intrusion Detection Systems (X-IDS): A Survey of Current Methods, Challenges, and Opportunities
Subash Neupane, Jesse Ables, William Anderson, Sudip Mittal, Shahram Rahimi, Ioana Banicescu, Maria Seale
Technical Challenge Emerging Opportunity Explainable Artificial Intelligence Intrusion Detection System Current Method Security Challenge

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 23, 2022

LBDMIDS: LSTM Based Deep Learning Model for Intrusion Detection Systems for IoT Networks
Kumar Saurabh, Saksham Sood, P. Aditya Kumar, Uphar Singh, Ranjana Vyas, O. P. Vyas, Rahamatullah Khondoker
Long Short Term Memory Intrusion Detection System Network Intrusion Detection Internet of Thing Network

June 21, 2022

Using EBGAN for Anomaly Intrusion Detection
Yi Cui, Wenfeng Shen, Jian Zhang, Weijia Lu, Chuang Liu, Lin Sun, Si Chen
Generative Adversarial Network Adversarial Learning Intrusion Detection Intrusion Detection System Based Intrusion Detection

Intrusion Detection System

Papers

Novelty Detection in Network Traffic: Using Survival Analysis for Feature Identification

DRL-GAN: A Hybrid Approach for Binary and Multiclass Network Intrusion Detection

Ensemble learning techniques for intrusion detection system in the context of cybersecurity

Intrusion Detection in Internet of Things using Convolutional Neural Networks

Anomaly Detection via Federated Learning

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

Effective Metaheuristic Based Classifiers for Multiclass Intrusion Detection

FastPacket: Towards Pre-trained Packets Embedding based on FastText for next-generation NIDS

Anomaly detection optimization using big data and deep learning to reduce false-positive

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

RX-ADS: Interpretable Anomaly Detection using Adversarial ML for Electric Vehicle CAN data

Improving Multilayer-Perceptron(MLP)-based Network Anomaly Detection with Birch Clustering on CICIDS-2017 Dataset

Designing an Artificial Immune System inspired Intrusion Detection System

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

Supervised Contrastive ResNet and Transfer Learning for the In-vehicle Intrusion Detection System

Creating an Explainable Intrusion Detection System Using Self Organizing Maps

Explainable Intrusion Detection Systems (X-IDS): A Survey of Current Methods, Challenges, and Opportunities

Robustness Evaluation of Deep Unsupervised Learning Algorithms for Intrusion Detection Systems

LBDMIDS: LSTM Based Deep Learning Model for Intrusion Detection Systems for IoT Networks

Using EBGAN for Anomaly Intrusion Detection