Integrating Grid with Intrusion Detection. - Fang-Yie Leu; Jia-Chun Lin; Ming-Chang Li; Chao-Tung Yang; Po-Chi Shih (AINA, 2005)

A Performance-Based Grid Intrusion Detection System. - Fang-Yie Leu; Jia-Chun Lin; Ming-Chang Li; Chao-Tung Yang (COMPSAC (1), 2005)

An Enhanced DGIDE Platform for Intrusion Detection. - Fang-Yie Leu; Fuu-Cheng Jiang; Ming-Chang Li; Jia-Chun Lin (ATC, 2007)

A Pollution Attack Resistant Multicast Authentication Scheme Tolerant to Packet Loss. - Warren W. Lin; Shiuhpyng Shieh; Jia-Chun Lin (SSIRI, 2008)

Lightweight, Distributed Key Agreement Protocol for Wireless Sensor Networks. - Che-Cheng Lin; Shiuhpyng Shieh; Jia-Chun Lin (SSIRI, 2008)

Detection workload in a dynamic grid-based intrusion detection environment. - Fang-Yie Leu; Ming-Chang Li; Jia-Chun Lin; Chao-Tung Yang (J. Parallel Distributed Comput., 2008)

Improving Data Grids Performance by Using Popular File Replicate First Algorithm. - Fang-Yie Leu; Ming-Chang Lee; Jia-Chun Lin (BWCCA, 2011)

A Semi-Preemptive Computational Service System with Limited Resources and Dynamic Resource Ranking. - Fang-Yie Leu; Keng-Yen Chao; Ming-Chang Lee; Jia-Chun Lin (Algorithms, 2012)

Deriving Job Completion Reliability and Job Energy Consumption for a General MapReduce Infrastructure from Single-Job Perspective. - Jia-Chun Lin; Fang-Yie Leu; Ming-Chang Lee; Ying-Ping Chen (AINA Workshops, 2013)

Analyzing job completion reliability and job energy consumption for a general MapReduce infrastructure. - Jia-Chun Lin; Fang-Yie Leu; Ying-Ping Chen (J. High Speed Networks, 2013)

Impact of MapReduce Task Re-execution Policy on Job Completion Reliability and Job Completion Time. - Jia-Chun Lin; Fang-Yie Leu; Ying-Ping Chen; Waqaas Munawar (AINA, 2014)

Scheduling MapReduce tasks on virtual MapReduce clusters from a tenant's perspective. - Jia-Chun Lin; Ming-Chang Lee; Ramin Yahyapour (IEEE BigData, 2014)

Proactive Distributed Digital Evidence Preservation with Tamper Resistance, Perfect Secrecy and High Survivability. - Jia-Chun Lin; Shiuhpyng Shieh; Chia-Wei Hsu (J. Inf. Sci. Eng., 2014)

PAReS: A Proactive and Adaptive Redundant System for MapReduce. - Jia-Chun Lin; Fang-Yie Leu; Ying-Ping Chen (J. Inf. Sci. Eng., 2015)

Analyzing job completion reliability and job energy consumption for a heterogeneous MapReduce cluster under different intermediate-data replication policies. - Jia-Chun Lin; Fang-Yie Leu; Ying-Ping Chen (J. Supercomput., 2015)

Impact of MapReduce Policies on Job Completion Reliability and Job Energy Consumption. - Jia-Chun Lin; Fang-Yie Leu; Ying-Ping Chen (IEEE Trans. Parallel Distributed Syst., 2015)

ABS-YARN: A Formal Framework for Modeling Hadoop YARN Clusters. - Jia-Chun Lin; Ingrid Chieh Yu; Einar Broch Johnsen; Ming-Chang Lee (FASE, 2016)

Comparing AWS Deployments Using Model-Based Predictions. - Einar Broch Johnsen; Jia-Chun Lin; Ingrid Chieh Yu (ISoLA (2), 2016)

Impacts of Task Re-Execution Policy on MapReduce Jobs. - Jia-Chun Lin; Fang-Yie Leu; Ying-Ping Chen (Comput. J., 2016)

Performance evaluation of job schedulers on Hadoop YARN. - Jia-Chun Lin; Ming-Chang Lee (Concurr. Comput. Pract. Exp., 2016)

Hybrid Job-Driven Scheduling for Virtual MapReduce Clusters. - Ming-Chang Lee; Jia-Chun Lin; Ramin Yahyapour (IEEE Trans. Parallel Distributed Syst., 2016)

A Model-Based Scalability Optimization Methodology for Cloud Applications. - Jia-Chun Lin; Jacopo Mauro; Thomas Brox Røst; Ingrid Chieh Yu (SC², 2017)

EasyChoose: A Continuous Feature Extraction and Review Highlighting Scheme on Hadoop YARN. - Ming-Chang Lee; Jia-Chun Lin; Olaf Owe (AINA, 2018)

Modeling and Simulation of Spark Streaming. - Jia-Chun Lin; Ming-Chang Lee; Ingrid Chieh Yu; Einar Broch Johnsen (AINA, 2018)

Privacy Mining from IoT-Based Smart Homes. - Ming-Chang Lee; Jia-Chun Lin; Olaf Owe (BWCCA, 2018)

A Framework for Flexible Program Evolution and Verification of Distributed Systems. - Olaf Owe; Elahe Fazeldehkordi; Jia-Chun Lin (MODELSWARD (Revised Selected Papers), 2019)

A Flexible Framework for Program Evolution and Verification. - Olaf Owe; Jia-Chun Lin; Elahe Fazeldehkordi (MODELSWARD, 2019)

PDS: Deduce elder privacy from smart homes. - Ming-Chang Lee; Jia-Chun Lin; Olaf Owe (Internet Things, 2019)

DALC: Distributed Automatic LSTM Customization for Fine-Grained Traffic Speed Prediction. - Ming-Chang Lee; Jia-Chun Lin (AINA, 2020)

RePAD: Real-Time Proactive Anomaly Detection for Time Series. - Ming-Chang Lee; Jia-Chun Lin; Ernst Gunnar Gran (AINA, 2020)

ReRe: A Lightweight Real-Time Ready-to-Go Anomaly Detection Approach for Time Series. - Ming-Chang Lee; Jia-Chun Lin; Ernst Gunner Gan (COMPSAC, 2020)

Distributed Fine-Grained Traffic Speed Prediction for Large-Scale Transportation Networks Based on Automatic LSTM Customization and Sharing. - Ming-Chang Lee; Jia-Chun Lin; Ernst Gunnar Gran (Euro-Par, 2020)

ReRe: A Lightweight Real-time Ready-to-Go Anomaly Detection Approach for Time Series. - Ming-Chang Lee; Jia-Chun Lin; Ernst Gunnar Gran (CoRR, 2020)

A configurable and executable model of Spark Streaming on Apache YARN. - Jia-Chun Lin; Ming-Chang Lee; Ingrid Chieh Yu; Einar Broch Johnsen (Int. J. Grid Util. Comput., 2020)

How Far Should We Look Back to Achieve Effective Real-Time Time-Series Anomaly Detection? - Ming-Chang Lee; Jia-Chun Lin; Ernst Gunnar Gran (AINA (1), 2021)

SALAD: Self-Adaptive Lightweight Anomaly Detection for Real-time Recurrent Time Series. - Ming-Chang Lee; Jia-Chun Lin; Ernst Gunnar Gran (COMPSAC, 2021)

DistTune: Distributed Fine-Grained Adaptive Traffic Speed Prediction for Growing Transportation Networks. - Ming-Chang Lee; Jia-Chun Lin; Ernst Gunnar Gran (CoRR, 2021)

NP-Free: A Real-Time Normalization-free and Parameter-tuning-free Representation Approach for Open-ended Time Series. - Ming-Chang Lee; Jia-Chun Lin; Volker Stolz (COMPSAC, 2023)

An Explainable Deep Learning-based Approach for Multivariate Time Series Anomaly Detection in IoT. - Aafan Ahmad Toor; Jia-Chun Lin; Ernst Gunnar Gran; Ming-Chang Lee (FIT, 2023)

Impact of Deep Learning Libraries on Online Adaptive Lightweight Time Series Anomaly Detection. - Ming-Chang Lee; Jia-Chun Lin (ICSOFT, 2023)

RoLA: A Real-Time Online Lightweight Anomaly Detection System for Multivariate Time Series. - Ming-Chang Lee; Jia-Chun Lin (ICSOFT, 2023)

RePAD2: Real-Time Lightweight Adaptive Anomaly Detection for Open-Ended Time Series. - Ming-Chang Lee; Jia-Chun Lin (IoTBDS, 2023)

Threats and Risk on Using Digital Technologies for Remote Health Care Process. - Pankaj Khatiwada; Muhammad Ali Fauzi; Bian Yang; Prosper Kandabongee Yeng; Jia-Chun Lin; Luyi Sun (SIET, 2023)

RePAD2: Real-Time, Lightweight, and Adaptive Anomaly Detection for Open-Ended Time Series. - Ming-Chang Lee; Jia-Chun Lin (CoRR, 2023)

Comparative Analysis of Real-Time Time Series Representation Across RNNs, Deep Learning Frameworks, and Early Stopping. - Ming-Chang Lee; Jia-Chun Lin; Sokratis K. Katsikas (KDIR, 2024)

Impact of Recurrent Neural Networks and Deep Learning Frameworks on Real-Time Lightweight Time Series Anomaly Detection. - Ming-Chang Lee; Jia-Chun Lin; Sokratis K. Katsikas (ICICS (1), 2024)

Investigating the Privacy Risk of Using Robot Vacuum Cleaners in Smart Environments. - Benjamin Ulsmåg; Jia-Chun Lin; Ming-Chang Lee (ICICS (1), 2024)

Evaluation of K-Means Time Series Clustering Based on Z-Normalization and NP-Free. - Ming-Chang Lee; Jia-Chun Lin; Volker Stolz (ICPRAM, 2024)

IoTective: Automated Penetration Testing for Smart Home Environments. - Kevin Nordnes; Jia-Chun Lin; Ming-Chang Lee; Victor Chang 001 (IoTBDS, 2024)

UoCAD: An Unsupervised Online Contextual Anomaly Detection Approach for Multivariate Time Series from Smart Homes. - Aafan Ahmad Toor; Jia-Chun Lin; Ming-Chang Lee; Ernst Gunnar Gran (IoTBDS, 2024)

GAD: A Real-Time Gait Anomaly Detection System with Online Adaptive Learning. - Ming-Chang Lee; Jia-Chun Lin; Sokratis K. Katsikas (SEC, 2024)

Exploring the effects of RNNs and deep learning frameworks on real-time, lightweight, adaptive time series anomaly detection. - Ming-Chang Lee; Jia-Chun Lin; Sokratis K. Katsikas (Concurr. Comput. Pract. Exp., 2024)

RePAD3: Advanced Lightweight Adaptive Anomaly Detection for Univariate Time Series of Any Pattern. - Ming-Chang Lee; Jia-Chun Lin; Sokratis K. Katsikas (ICAART (2), 2025)

PacketZapper: A Scalable and Automated Platform for IoT Traffic Collection and Analysis. - Mathias Fredrik Hedberg; Jia-Chun Lin; Ming-Chang Lee (IoTBDS, 2025)

UoCAD2: An unsupervised online contextual anomaly detection approach using optimized hyperparameters of RNNs for multivariate time series. - Aafan Ahmad Toor; Jia-Chun Lin; Ernst Gunnar Gran (Internet Things, 2025)

Exploring the impact of Optimised Hyperparameters on Bi-LSTM-based Contextual Anomaly Detector. - Aafan Ahmad Toor; Jia-Chun Lin; Ernst Gunnar Gran (CoRR, 2025)