Ying‐Dar Lin
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View article: Production of high-quality bleached chemi-mechanical pulp from moso bamboo via an improved pre-conditioning refiner chemical alkaline peroxide mechanical pulping process
Production of high-quality bleached chemi-mechanical pulp from moso bamboo via an improved pre-conditioning refiner chemical alkaline peroxide mechanical pulping process Open
Moso bamboo is a fast-growing, abundant resource with significant potential as a sustainable alternative to wood for pulp production. However, traditional kraft pulping of moso bamboo faces challenges such as low yield, high pollutant load…
View article: Beyond Natural Language Perplexity: Detecting Dead Code Poisoning in Code Generation Datasets
Beyond Natural Language Perplexity: Detecting Dead Code Poisoning in Code Generation Datasets Open
The increasing adoption of large language models (LLMs) for code-related tasks has raised concerns about the security of their training datasets. One critical threat is dead code poisoning, where syntactically valid but functionally redund…
View article: Layer-Aware Task Arithmetic: Disentangling Task-Specific and Instruction-Following Knowledge
Layer-Aware Task Arithmetic: Disentangling Task-Specific and Instruction-Following Knowledge Open
Large language models (LLMs) demonstrate strong task-specific capabilities through fine-tuning, but merging multiple fine-tuned models often leads to degraded performance due to overlapping instruction-following components. Task Arithmetic…
View article: Evaluating Cyber Threat Intelligence: Accuracy, Completeness, Relevance, and Freshness
Evaluating Cyber Threat Intelligence: Accuracy, Completeness, Relevance, and Freshness Open
In the realm of cybersecurity, the extraction of Cyber Threat Intelligence (CTI) is vital for acquiring accurate Tactics, Techniques, and Procedures (TTPs) and Indicators of Compromise (IoC) from reputable sources. The extracted CTI must b…
View article: Evolving ML-Based Intrusion Detection: Cyber Threat Intelligence for Dynamic Model Updates
Evolving ML-Based Intrusion Detection: Cyber Threat Intelligence for Dynamic Model Updates Open
Existing Intrusion Detection System (IDS) relies on pre-trained models that struggle to keep pace with the evolving nature of network threats, as they cannot detect new types of network attacks until updated. Cyber Threat Intelligence (CTI…
View article: Deep Reinforcement Learning-Based Adaptive Nulling in Phased Array Under Dynamic Environments
Deep Reinforcement Learning-Based Adaptive Nulling in Phased Array Under Dynamic Environments Open
A phased array consists of multiple antenna elements that can control the direction of the radiated signal by adjusting each antenna element’s phase and amplitude, which are encapsulated in the phased array weights. To obtain better commun…
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: Quality Analysis in IDS Dataset: Impact on Model Generalization
Quality Analysis in IDS Dataset: Impact on Model Generalization Open
Intrusion Detection Systems (IDS) utilizing machine learning (ML) are essential for detecting network intrusions. A key challenge in ML-based IDS is ensuring models can generalize effectively—accurately classifying unseen data. This abilit…
View article: Improving Generalization of ML-Based IDS With Lifecycle-Based Dataset, Auto-Learning Features, and Deep Learning
Improving Generalization of ML-Based IDS With Lifecycle-Based Dataset, Auto-Learning Features, and Deep Learning Open
During the past 10 years, researchers have extensively explored the use of machine learning (ML) in enhancing network intrusion detection systems (IDS). While many studies focused on improving accuracy of ML-based IDS, true effectiveness l…
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: P4toNFV: Offloading from P4 switches to NFV in programmable data planes
P4toNFV: Offloading from P4 switches to NFV in programmable data planes Open
Summary P4 combines the benefits of hardware‐based networking with the adaptability of software‐based network operations. However, when faced with intricate network functions, P4 switches reveal constraints in memory and processing primiti…
View article: Understanding Privacy Risks of High-accuracy Radio Positioning and Sensing in Wireless Networks
Understanding Privacy Risks of High-accuracy Radio Positioning and Sensing in Wireless Networks Open
High-accuracy radio positioning and sensing technologies are crucial for many applications, including tracking hospital patients and identifying victims during emergency calls. However, these techniques present serious privacy concerns sin…
View article: Understanding Privacy Risks of High-accuracy Radio Positioning and Sensing in Wireless Networks
Understanding Privacy Risks of High-accuracy Radio Positioning and Sensing in Wireless Networks Open
High-accuracy radio positioning and sensing technologies are crucial for many applications, including tracking hospital patients and identifying victims during emergency calls. However, these techniques present serious privacy concerns sin…
View article: A Novel Multi-Stage Approach for Hierarchical Intrusion Detection
A Novel Multi-Stage Approach for Hierarchical Intrusion Detection Open
An intrusion detection system (IDS), traditionally an example of an effective security monitoring system, is facing significant challenges due to the ongoing digitization of our modern society. The growing number and variety of connected d…
View article: Resource Management in LADNs Supporting 5G V2X Communications
Resource Management in LADNs Supporting 5G V2X Communications Open
Local access data networks (LADNs) are promising paradigms for reducing latency, decreasing energy consumption, and improving the quality of service (QoS) of fifth-generation (5G) radio access networks (RANs) that support vehicle-to-everyt…
View article: Offloading in P4 Switch Integrated with Multiple Virtual Network Function Servers
Offloading in P4 Switch Integrated with Multiple Virtual Network Function Servers Open
Software Defined Networking (SDN) and Network Function Virtualization (NFV) are two transformative technologies that offer distinct benefits. SDN virtualizes the control plane by separating it from the data plane, while NFV virtualizes the…
View article: ICITDA 2022 Cover Page
ICITDA 2022 Cover Page Open
Intrusions have increasingly long kill chains, with various footprints left for detection and investigation, and thus require machine learning to better recognize them.These footprints include threat intelligence in IP's and domains, netwo…
View article: ICITDA 2022 Cover Page
ICITDA 2022 Cover Page Open
ICITDA 2022 is a hybrid (online-onsite) conference held on the 4th and 5th of November in Yogyakarta, Indonesia, with the theme "Bridging the Challenges in Network Security and Digital Forensics".Our hope and grand objective are to provide…
View article: Task Assignment and Capacity Allocation for ML-Based Intrusion Detection as a Service in a Multi-Tier Architecture
Task Assignment and Capacity Allocation for ML-Based Intrusion Detection as a Service in a Multi-Tier Architecture Open
Intrusion Detection Systems (IDS) play an important role in detecting network intrusions. Because intrusions have many variants and zero-day attacks, traditional signature- and anomaly-based IDS often fail to detect them. On the other hand…
View article: Linked PDF of Table of Contents
Linked PDF of Table of Contents Open
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View article: A Survey on Offloading in Federated Cloud-Edge-Fog Systems with Traditional Optimization and Machine Learning
A Survey on Offloading in Federated Cloud-Edge-Fog Systems with Traditional Optimization and Machine Learning Open
The huge amount of data generated by the Internet of things (IoT) devices needs the computational power and storage capacity provided by cloud, edge, and fog computing paradigms. Each of these computing paradigms has its own pros and cons.…