Intrusion prevention system
View article: Integration of Wazuh and Suricata with Telegram for Enhanced Threat Detection and Multiple Attack Notifications
Integration of Wazuh and Suricata with Telegram for Enhanced Threat Detection and Multiple Attack Notifications Open
The rise of connected devices over the internet has led to an increase in attacks on users, compromising their information exchange and revealing sensitive data. Modern cyber threats are becoming increasingly sophisticated and severe, taki…
View article: ENHANCING NETWORK SECURITY IN SDN ENVIRONMENTS: DEVELOPING A DEEP LEARNING-BASED INTRUSION DETECTION SYSTEM FOR EFFECTIVE ANOMALY DETECTION
ENHANCING NETWORK SECURITY IN SDN ENVIRONMENTS: DEVELOPING A DEEP LEARNING-BASED INTRUSION DETECTION SYSTEM FOR EFFECTIVE ANOMALY DETECTION Open
View article: ENHANCING NETWORK SECURITY IN SDN ENVIRONMENTS: DEVELOPING A DEEP LEARNING-BASED INTRUSION DETECTION SYSTEM FOR EFFECTIVE ANOMALY DETECTION
ENHANCING NETWORK SECURITY IN SDN ENVIRONMENTS: DEVELOPING A DEEP LEARNING-BASED INTRUSION DETECTION SYSTEM FOR EFFECTIVE ANOMALY DETECTION Open
View article: aallhhuussaaiin444-arch/FP2-IDS: Federated Privacy-Preserving Intrusion Detection System for Cloud–IoT Convergence
aallhhuussaaiin444-arch/FP2-IDS: Federated Privacy-Preserving Intrusion Detection System for Cloud–IoT Convergence Open
Federated Privacy-Preserving Intrusion Detection System for Cloud–IoT Convergence
View article: aallhhuussaaiin444-arch/FP2-IDS: Federated Privacy-Preserving Intrusion Detection System for Cloud–IoT Convergence
aallhhuussaaiin444-arch/FP2-IDS: Federated Privacy-Preserving Intrusion Detection System for Cloud–IoT Convergence Open
Federated Privacy-Preserving Intrusion Detection System for Cloud–IoT Convergence
View article: Deep Learning-Based Fog-Cloud Approach Intrusion Detection System in IoMT
Deep Learning-Based Fog-Cloud Approach Intrusion Detection System in IoMT Open
View article: AI-driven intrusion detection and lightweight authentication framework for secure and efficient medical sensor networks
AI-driven intrusion detection and lightweight authentication framework for secure and efficient medical sensor networks Open
View article: PAMO: Pattern Matching Offload for Intrusion Detection Systems
PAMO: Pattern Matching Offload for Intrusion Detection Systems Open
View article: DESIGN AND ARCHITECTURE OF PERIMETER DEFENCE INTRUSION DETECTION SYSTEMS BASED ON UGV
DESIGN AND ARCHITECTURE OF PERIMETER DEFENCE INTRUSION DETECTION SYSTEMS BASED ON UGV Open
Defense Intrusion Detection Systems (DIDS) are specialized subsets of intrusion detection systems tailored specifically for military and national security purposes. The proposed research is focused on the design and architecture of mobile …
View article: GEM-CAN: Real-World CAN-Bus Attack Scenarios on an Autonomous Vehicle for Intrusion Detection
GEM-CAN: Real-World CAN-Bus Attack Scenarios on an Autonomous Vehicle for Intrusion Detection Open
This dataset provides labeled CAN-bus traffic captured from a GEM e6 autonomous vehicle under normal operation and controlled cyberattacks. It includes ~143K frames spanning nominal driving (~100K), DoS floods using ID 0x00000000 (~41K), a…
View article: GEM-CAN: Real-World CAN-Bus Attack Scenarios on an Autonomous Vehicle for Intrusion Detection
GEM-CAN: Real-World CAN-Bus Attack Scenarios on an Autonomous Vehicle for Intrusion Detection Open
This dataset provides labeled CAN-bus traffic captured from a GEM e6 autonomous vehicle under normal operation and controlled cyberattacks. It includes ~143K frames spanning nominal driving (~100K), DoS floods using ID 0x00000000 (~41K), a…
View article: DESIGN AND ARCHITECTURE OF PERIMETER DEFENCE INTRUSION DETECTION SYSTEMS BASED ON UGV
DESIGN AND ARCHITECTURE OF PERIMETER DEFENCE INTRUSION DETECTION SYSTEMS BASED ON UGV Open
Defense Intrusion Detection Systems (DIDS) are specialized subsets of intrusion detection systems tailored specifically for military and national security purposes. The proposed research is focused on the design and architecture of mobile …
View article: Amina-SAHBI/Intrusion-Detection-Benchmarking-on-SDN-Net-Dataset: SDN-Net Release
Amina-SAHBI/Intrusion-Detection-Benchmarking-on-SDN-Net-Dataset: SDN-Net Release Open
Intrusion Detection Benchmarking on SDN-Net Dataset provides implementation and evaluation of 12 classifiers for intrusion detection on flow-level traffic. Models include Random Forest, Decision Tree, KNN, Naïve Bayes, SVM, Gradient Boosti…
View article: Amina-SAHBI/Intrusion-Detection-Benchmarking-on-SDN-Net-Dataset: SDN-Net Release
Amina-SAHBI/Intrusion-Detection-Benchmarking-on-SDN-Net-Dataset: SDN-Net Release Open
Intrusion Detection Benchmarking on SDN-Net Dataset provides implementation and evaluation of 12 classifiers for intrusion detection on flow-level traffic. Models include Random Forest, Decision Tree, KNN, Naïve Bayes, SVM, Gradient Boosti…
View article: PROSPECTS FOR THE USE OF ARTIFICIAL INTELLIGENCE IN MONITORING AND SECURITY SYSTEMS OF CORPORATE NETWORKS
PROSPECTS FOR THE USE OF ARTIFICIAL INTELLIGENCE IN MONITORING AND SECURITY SYSTEMS OF CORPORATE NETWORKS Open
This work explores the use of artificial intelligence and machine learning techniques to enhance the monitoring and security of modern corporate networks. It provides an overview of traditional signature-based intrusion detection methods a…
View article: PROSPECTS FOR THE USE OF ARTIFICIAL INTELLIGENCE IN MONITORING AND SECURITY SYSTEMS OF CORPORATE NETWORKS
PROSPECTS FOR THE USE OF ARTIFICIAL INTELLIGENCE IN MONITORING AND SECURITY SYSTEMS OF CORPORATE NETWORKS Open
This work explores the use of artificial intelligence and machine learning techniques to enhance the monitoring and security of modern corporate networks. It provides an overview of traditional signature-based intrusion detection methods a…
View article: A hybrid lightweight feature extraction assisted ensemble approach for intrusion detection with ESMOTE-based class imbalance handling in IoT networks
A hybrid lightweight feature extraction assisted ensemble approach for intrusion detection with ESMOTE-based class imbalance handling in IoT networks Open
View article: Study of Attacks on IoT Infrastructure and Protective Technologies
Study of Attacks on IoT Infrastructure and Protective Technologies Open
The rapid expansion of Internet of Things (IoT) infrastructure has introduced unprecedented opportunities across industries, while simultaneously exposing systems to diverse cyber threats. This study investigates prevalent attack vectors t…
View article: SDN-Net: A Novel Dataset for Intrusion Detection within SDN/NFV Network
SDN-Net: A Novel Dataset for Intrusion Detection within SDN/NFV Network Open
This dataset, SDN-Net, is created specifically for AI-driven intrusion detection research within programmable SDN/NFV environments. SDN-Net offers the scale and attack diversity required to benchmark Machine Learning and Deep Learning mode…
View article: SDN-Net: A Novel Dataset for Intrusion Detection within SDN/NFV Network
SDN-Net: A Novel Dataset for Intrusion Detection within SDN/NFV Network Open
This dataset, SDN-Net, is created specifically for AI-driven intrusion detection research within programmable SDN/NFV environments. SDN-Net offers the scale and attack diversity required to benchmark Machine Learning and Deep Learning mode…
View article: ADVERSARIAL ROBUSTNESS OF DEEP LEARNING-BASED INTRUSION DETECTION SYSTEMS AGAINST AI-POWERED CYBER ATTACKS
ADVERSARIAL ROBUSTNESS OF DEEP LEARNING-BASED INTRUSION DETECTION SYSTEMS AGAINST AI-POWERED CYBER ATTACKS Open
View article: Study of Attacks on IoT Infrastructure and Protective Technologies
Study of Attacks on IoT Infrastructure and Protective Technologies Open
The rapid expansion of Internet of Things (IoT) infrastructure has introduced unprecedented opportunities across industries, while simultaneously exposing systems to diverse cyber threats. This study investigates prevalent attack vectors t…
View article: ADVERSARIAL ROBUSTNESS OF DEEP LEARNING-BASED INTRUSION DETECTION SYSTEMS AGAINST AI-POWERED CYBER ATTACKS
ADVERSARIAL ROBUSTNESS OF DEEP LEARNING-BASED INTRUSION DETECTION SYSTEMS AGAINST AI-POWERED CYBER ATTACKS Open
View article: Human-In-The-Loop Threat Detection
Human-In-The-Loop Threat Detection Open
The increasing complexity of cyber threats has made automated systems essential for detecting and preventing malicious activities. However, fully automated models often struggle to handle ambiguous or novel attacks that require contextual …
View article: "CAN-FD Intrusion Detection Dataset"
"CAN-FD Intrusion Detection Dataset" Open
"This dataset contains Controller Area Network Flexible Data Rate (CAN-FD) traffic collected from production vehicles released in 2021. CAN-FD extends classical CAN by supporting longer payloads and higher data rates, and has become widely…
View article: "M-CAN Intrusion Detection Dataset"
"M-CAN Intrusion Detection Dataset" Open
"This dataset contains Controller Area Network (CAN) traffic collected from the M-CAN bus of a Genesis G80 vehicle. M-CAN is a mid-speed bus responsible for communication with navigation systems, multimedia devices, and related in-vehicle …
View article: Deep Reinforcement Learning-Based Network Intrusion Prevention in Cloud-Edge Architectures
Deep Reinforcement Learning-Based Network Intrusion Prevention in Cloud-Edge Architectures Open
Cloud-edge architectures enable low-latency distributed data processing but introduce complex attack surfaces that challenge traditional Network Intrusion Detection and Prevention Systems (NIDPS). Conventional systems relying on static sig…
View article: Deep Reinforcement Learning-Based Network Intrusion Prevention in Cloud-Edge Architectures
Deep Reinforcement Learning-Based Network Intrusion Prevention in Cloud-Edge Architectures Open
Cloud-edge architectures enable low-latency distributed data processing but introduce complex attack surfaces that challenge traditional Network Intrusion Detection and Prevention Systems (NIDPS). Conventional systems relying on static sig…
View article: "CAN Intrusion Detection Dataset"
"CAN Intrusion Detection Dataset" Open
"This dataset provides raw Controller Area Network (CAN) traffic collected from a real vehicle (KIA Soul) under four states: DoS attack, Fuzzy attack, Impersonation attack, and normal driving conditions. The data were captured via the OBD-…
View article: "B-CAN Intrusion Dataset"
"B-CAN Intrusion Dataset" Open
"This dataset contains Controller Area Network (CAN) traffic collected from the B-CAN bus of a Genesis G80 vehicle. B-CAN is a low-speed in-vehicle network used for body-control\u2013related functions such as BCM lighting, power windows, a…