Nong Ye, Ph.D.

INTRODUCTION

CURRICULUM VITAE

PUBLICATIONS

RESEARCH AWARDS

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Secure Computer and Network Systems : Modeling, Analysis and Design by Nong Ye
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NONG YE, Ph.D.

Professor, Department of Industrial Engineering

Director, Cluster on Data Exploration and Modeling for Brain Science

Director, Information and Systems Assurance Laboratory

Ira A. Fulton School of Engineering

ARIZONA STATE UNIVERSITY

Box 875906, Tempe, AZ 85287

Phone: (480) 965-7812, Fax: (480) 965-8692

Email: nongye@asu.edu, URL: http://enpub.fulton.asu.edu/ye/

 

INTRODUCTION

 

Dr. Nong Ye is a Professor of Industrial Engineering at Arizona State University (ASU), Tempe, Arizona. Dr. Ye received her Ph.D. degree (1991) in Industrial Engineering from Purdue University, West Lafayette, Indiana, and her M.S. degree (1988) and B.S. degree (1985) in Computer Science from the Chinese Academy of Sciences and Peking University in P. R. China, respectively.

Dr. Ye's past and current research activities, which have received over $8M external funding support and have produced seventy-six journal papers and three books (including Secure Computer and Network Systems: Modeling, Analysis and Design and The Handbook of Data Mining), fall into the following two areas.

·        Data and knowledge exploration, involving the following data and applications.

o       Computer and network data for real-time decision making to detect and assess cyber attacks and security risks on computer and network systems. Through data mining, statistical analysis and data modeling, attack-sensitive data variables are selected, statistical and mathematical features of data are extracted and examined to discover distinctive univariate and multivariate characteristics of cyber attack data, data models are defined to represent discovered data characteristics, and detection and assessment algorithms which incorporate data models are developed.

Two examples of sponsored research projects:

§         U. S. Intelligence Community Advanced Research and Development Activities/Air Force Research Laboratory, September 2003 – February 2005, $799,576, N. Ye (PI), “Cyber Signal/Noise Characteristics and Sensor Models for Early Cyber Indications and Warning.”

§         Defense Advanced Research Projects Agency, May 1999 – May 2001, $612,083, N. Ye (PI), “The Monitoring, Detection, Isolation and Assessment of Information Warfare Attacks through Multi-Level, Multi-Scale System Modeling and Model-based Technology.”

Two examples of publications:

§         X. Li, and N. Ye, “A supervised clustering and classification algorithm for mining data with mixed variables.” IEEE Transactions on Systems, Man, and Cybernetics, Part A, Vol. 36, No. 2, 2006, pp. 396-406.

§         N. Ye, Q. Chen, and C. Borror, “EWMA forecast of normal system activity for computer intrusion detection.” IEEE Transactions on Reliability, Vol. 53, No. 4, 2004, pp. 557-566.

o       Cognitive behavioral data for human-computer interface design. Through experimental design, statistical hypothesis testing and data mining, human behavioral and performance data in computer programming and manufacturing assembly tasks are collected and analyzed to understand expert-novice differences in knowledge representation which are then used to design user-friendly computer interface.

Two examples of sponsored research projects:

§         Office of Naval Research, October 1992 – September 1995, $730,000, N. Ye (co-PI), “MURI: Three-Dimensional Visualization and Interaction for the Design of Large-Scale Manufactured Objects.”

§         National Science Foundation, September 1992 – February 1996, $90,000, N. Ye (PI), “A Cognitive Engineering Approach to the Interface Design of Decision Support Systems for Machine Fault Diagnosis.”

Two examples of publications:

§         N. Ye, P. Banerjee, A. Banerjee, and F. Dech, “A comparative study of assembly planning in traditional and virtual environments.” IEEE Transactions on Systems, Man, and Cybernetics, Vol. 29, No. 4, 1999, pp. 546-555.

§         N. Ye, “The MDS-ANAVA technique for assessing knowledge representation differences between skill groups.” IEEE Transactions on Systems, Man and Cybernetics, Vol. 28, No. 5, 1998, pp. 586-600.

o       Biomedical data for brain science with applications in Brain-Machine Interface (BMI) for assisting people who have lost motor or sensory function and in prediction and treatment of brain-related diseases such as the Alzheimer disease and brain tumors. Through data mining, statistical analysis and data modeling, brain data (including electrical spike waveforms and structural/functional images) are analyzed to discover statistical/mathematical features and characteristics of brain neuron population dynamics, and data models are defined accordingly and employed in applications for BMI and disease prediction/treatment.

One example of sponsored research:

§         Ira A. Fulton School of Engineering, February 2007 - February 2009, N. Ye (Director), "Cluster of Data Exploration and Modeling for Brain Science."

o       Urban system and environment data for urban system sustainability. Through data mining, statistical analysis and data modeling, urban metabolic flow data (including data about water, materials, energy, waste, air quality, etc.) are analyzed to understand interrelationships of urban systems and to design sustainable urban system infrastructures.

·        Optimization and quality control of system process and operations, involving the following systems.

o       Computer and network systems for dependability, especially service stability and end-to-end delay guarantee. Though modeling, simulation and optimization of job scheduling, admission control and resource reservation, job waiting time variance is minimized at local and regional levels of computer and network services, and end-to-end delay guarantee is enabled at the global level of computer and network services.

Two examples of sponsored research projects:

§         Department of Defense and Air Force Office of Scientific Research, May 2001 – December 2006, $2,133,095, N. Ye (PI), “MURI CIP: A Complex Adaptive System Approach to QoS Assurance and Stateful Resource Management for Dependable Information Infrastructure.”

§         National Science Foundation, October 1998 – September 2003, $2,000,000, N. Ye (co-PI), “CAVERN - The CAVE Research Network.”

Two examples of publications:

§         X. Xu, and N. Ye, “Minimization of job waiting time variance on identical parallel machines.” IEEE Transactions on Systems, Man, and Cybernetics, Part C, in press.

§         N. Ye, Z. Yang, Y.-C. Lai, and Toni Farley, “Enhancing router QoS through job scheduling with weighted shortest processing time—adjusted.” Computers & Operations Research, Vol. 32, No. 9, 2005, pp. 2255-2269.