Po‐Ching Lin
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View article: From Flow to Packet: A Unified Machine Learning Approach for Advanced Intrusion Detection
From Flow to Packet: A Unified Machine Learning Approach for Advanced Intrusion Detection Open
In the era of advanced networking with 5G integration, the need for efficient and scalable intrusion detection systems has become critical to securing large‐scale digital infrastructures. Traditional intrusion detection approaches either a…
View article: Privacy-Preserving Federated Learning for Intrusion Detection in IoT Environments: A Survey
Privacy-Preserving Federated Learning for Intrusion Detection in IoT Environments: A Survey Open
With the rapid development of artificial intelligence and a new generation of network technologies, the Internet of Things (IoT) is expanding worldwide. Malicious agents consistently exploit new technical vulnerabilities to access the vari…
View article: Clustering APT Groups Through Cyber Threat Intelligence by Weighted Similarity Measurement
Clustering APT Groups Through Cyber Threat Intelligence by Weighted Similarity Measurement Open
Advanced Persistent Threat (APT) groups pose significant cybersecurity threats due to their sophisticated and persistent nature. This study introduces a novel methodology to understand their collaborative patterns and shared objectives, wh…
View article: Deep Learning-based Localization and Outlier Removal Integration Model for Indoor Surveillance
Deep Learning-based Localization and Outlier Removal Integration Model for Indoor Surveillance Open
Directional antenna technologies are crucial to enhance high-speed data transmission in emerging wireless communications such as mmWave. These technologies can enable high-accuracy radio positioning by exploiting spatial-temporal signal pr…
View article: Deep Learning-based Localization and Outlier Removal Integration Model for Indoor Surveillance
Deep Learning-based Localization and Outlier Removal Integration Model for Indoor Surveillance Open
Directional antenna technologies are crucial to enhance high-speed data transmission in emerging wireless communications such as mmWave. These technologies can enable high-accuracy radio positioning by exploiting spatial-temporal signal pr…
View article: Towards the Age of Intelligent Vehicular Networks for Connected and Autonomous Vehicles in 6G
Towards the Age of Intelligent Vehicular Networks for Connected and Autonomous Vehicles in 6G Open
Twenty-two years after the advent of the first-generation vehicular network, i.e., dedicated short-range communications (DSRC) standard/IEEE 802.11p, the vehicular technology market has become very competitive with a new player, Cellular V…
View article: Machine Learning With Variational AutoEncoder for Imbalanced Datasets in Intrusion Detection
Machine Learning With Variational AutoEncoder for Imbalanced Datasets in Intrusion Detection Open
As a result of the explosion of security attacks and the complexity of modern networks, machine learning (ML) has recently become the favored approach for intrusion detection systems (IDS). However, the ML approach usually faces three chal…
View article: Robust Positioning-based Verification Scheme for Enhancing Reliability of Vehicle Platoon Control
Robust Positioning-based Verification Scheme for Enhancing Reliability of Vehicle Platoon Control Open
Vehicle platooning is a promising technology to bring up significant benefits of improved fuel economy and fewer traffic collisions. However, many security attacks such as beacon message falsification have been exposed, creating grave conc…
View article: Security and Privacy for 6G: A Survey on Prospective Technologies and Challenges
Security and Privacy for 6G: A Survey on Prospective Technologies and Challenges Open
Sixth-generation (6G) mobile networks will have to cope with diverse threats on a space-air-ground integrated network environment, novel technologies, and an accessible user information explosion. However, for now, security and privacy iss…
View article: An Unsupervised Deep Learning Model for Early Network Traffic Anomaly Detection
An Unsupervised Deep Learning Model for Early Network Traffic Anomaly Detection Open
Various attacks have emerged as the major threats to the success of a connected world like the Internet of Things (IoT), in which billions of devices interact with each other to facilitate human life. By exploiting the vulnerabilities of c…
View article: A Beamforming Signal-Based Verification Scheme for Data Sharing in 5G Vehicular Networks
A Beamforming Signal-Based Verification Scheme for Data Sharing in 5G Vehicular Networks Open
Vehicle-to-Everything (V2X) communications are vital for autonomous vehicles to share sensing data about the surrounding environment, particularly in non-line-of-sight (NLOS) areas where the camera and radar systems often perform poorly. H…
View article: Preventing the attempts of abusing cheap-hosting Web-servers for monetization attacks
Preventing the attempts of abusing cheap-hosting Web-servers for monetization attacks Open
Over the past decades, the web is always one of the most popular targets of hackers. Today, along with the popular usage of open sources such as Wordpress and Joomla, the explosion of the vulnerabilities in such frameworks causes the websi…
View article: Energy Depletion Attacks in Low Power Wireless Networks
Energy Depletion Attacks in Low Power Wireless Networks Open
Low Power Wireless (LPW) networks have recently been emerging as key candidates to offer affordable connectivity for the constrained devices in the Internet of Things (IoT). However, they also raise major security concerns due to the inher…
View article: Toward Optimal Resource Allocation of Virtualized Network Functions for Hierarchical Datacenters
Toward Optimal Resource Allocation of Virtualized Network Functions for Hierarchical Datacenters Open
Telecommunications service providers (TSPs) previously provided network functions to end users with dedicated hardware, but they are resorting to virtualized infrastructure for reducing costs and increasing flexibility in resource allocati…
View article: Unintentional and Involuntary Personal Information Leakage on Facebook from User Interactions
Unintentional and Involuntary Personal Information Leakage on Facebook from User Interactions Open
Online social networks (OSNs) have changed the way people communicate with each other.An OSN usually encourages the participants to provide personal information such as real names, birthdays and educational background to look for and estab…