A survey on feature selection techniques based on filtering methods for cyber attack detection
Y Lyu, Y Feng, K Sakurai - Information, 2023 - mdpi.com
Cyber attack detection technology plays a vital role today, since cyber attacks have been
causing great harm and loss to organizations and individuals. Feature selection is a …
causing great harm and loss to organizations and individuals. Feature selection is a …
Deep Learning-Based Anomaly Detection in Network Traffic for Cyber Threat Identification
An essential aspect of cybersecurity is the continuously growing threat landscape, which
necessitates the use of advanced anomaly detection techniques in network data. The …
necessitates the use of advanced anomaly detection techniques in network data. The …
Multi-Resolution Analysis with Visualization to Determine Network Attack Patterns
Analyzing network traffic activities is imperative in network security to detect attack patterns.
Due to the complex nature of network traffic event activities caused by continuously …
Due to the complex nature of network traffic event activities caused by continuously …
The opportunity in difficulty: A dynamic privacy budget allocation mechanism for privacy-preserving multi-dimensional data collection
Data collection under local differential privacy (LDP) has been gradually on the stage.
Compared with the implementation of LDP on the single attribute data collection, that on …
Compared with the implementation of LDP on the single attribute data collection, that on …
Cost-Efficient Feature Selection for Horizontal Federated Learning
S Banerjee, D Bhuyan, E Elmroth… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Horizontal federated learning (HFL) exhibits substantial similarities in feature space across
distinct clients. However, not all features contribute significantly to the training of the global …
distinct clients. However, not all features contribute significantly to the training of the global …
INTELLECT: Adapting Cyber Threat Detection to Heterogeneous Computing Environments
The widespread adoption of cloud computing, edge, and IoT has increased the attack
surface for cyber threats. This is due to the large-scale deployment of often unsecured …
surface for cyber threats. This is due to the large-scale deployment of often unsecured …
Cyber Attacks Prevention Towards Prosumer-Based EV Charging Stations: An Edge-Assisted Federated Prototype Knowledge Distillation Approach
In this paper, cyber-attack prevention for the prosumer-based electric vehicle (EV) charging
stations (EVCSs) is investigated, which covers two aspects: 1) cyber-attack detection on …
stations (EVCSs) is investigated, which covers two aspects: 1) cyber-attack detection on …
[HTML][HTML] Machine Learning-Based Network Anomaly Detection: Design, Implementation, and Evaluation
Background: In the last decade, numerous methods have been proposed to define and
detect outliers, particularly in complex environments like networks, where anomalies …
detect outliers, particularly in complex environments like networks, where anomalies …
Feature extraction of high-dimensional data based on J-HOSVD for cyber-physical-social systems
With the further integration of Cyber-Physical-Social systems (CPSSs), there is explosive
growth of the data in CPSSs. How to discover effective information or knowledge from …
growth of the data in CPSSs. How to discover effective information or knowledge from …
Interactive Web-Based Visual Analysis on Network Traffic Data
Network traffic data analysis is important for securing our computing environment and data.
However, analyzing network traffic data requires tremendous effort because of the …
However, analyzing network traffic data requires tremendous effort because of the …