Qutaibah Althebyan, Ph.D

Dean, College of Engineering

Al Ain Campus

+97137024880

Engineering@aau.ac.ae

Biography

Dr. Qutaibah Althebyan is an associate professor and Dean of College of Engineering at Al Ain University, UAE. He has been there since January 2018. Prior to joining Al Ain University, he was an associate professor of Software Engineering at Jordan University of Science and Technology (JUST) since August of 2008. Dr. Qutaibah Althebyan finished his Ph.D. degree in 2008 in Computer Science from University of Arkansas - Fayetteville and his Master degree in 2004 in Computer Information Systems from the University of Michigan – Dearborn. Dr. Althebyan published several papers in high ranked journals and conferences. He is also a reviewer for many journals and conferences. Dr. Althebyan main research interests are, but not limited to, in information security, database security, security in the cloud, big data management, health information systems, information assurance, software metrics and quality of open-source systems. Lately, he has been working in different security, e-health and software engineering projects, namely; Large Scale Insider Threat Assessments and damage assessment in the cloud in the area of cloud security.

Education

PhD Computer Science, University of Arkansas – Fayetteville, USA

MSc Computer Science, University of Michigan – Dearborn, USA

BSc System Programming, Jordan University of Science and Technology - Irbed, Jordan

Research Interests

Software security, cloud computing and cloud security, insider threat in the cloud, database and database security, software engineering especially object – oriented software metrics, health information system especially finding solutions for health problems that are intersected with cloud computing.

Selected Publications

Conferences

  • Qutaibah Althebyan, “A Mobile Edge Mitigation Model for Insider Threats: A Knowledgebase Approach”. Accepted for publication in the Proceeding of the 20th International Arab Conference on Information Technology (ACIT'2019), UAE, Dec 2019.
  • Hassan Najadat, Qutaibah Althebyan, Yasmin Al-Omary, “Higher Education Units Assessment Based on Data Envelopment Analysis and Clustering Techniques”. Accepted for publication in the Proceeding of the 20th International Arab Conference on Information Technology (ACIT'2019), UAE, Dec 2019.
  • Huthifh Al-Rushdan, Mohammad Shurman, Sharhabeel H. Alnabelsi, Qutaibah Althebyan, “Zero-Day Attack Detection and Prevention in Software-Defined Networks”. Accepted for publication in the Proceeding of the 20th International Arab Conference on Information Technology (ACIT'2019), UAE, Dec 2019.
  • Mohammad Al-Zinati, Qutaibah Althebyan, Yaser Jararweh, “An Agent Based Model for Health Surveillance Systems and Early Biological Threat Detection”, 2018 IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud), Spain, August 6 – 8, 2018
  • Hassan Najadat, Qutaibah Althebyan, Abedallah Khamaisehy, Mohammad Al-Saady and Ahmad Al Rawashdeh. “Efficiency Analysis of Health Care Centers Using Data Envelopment Analysis”, In Proceedings of the 4th IEEE International Conference on Computer Science, Computer Engineering, and Education Technologies (CSCEET2017), Beirut, Lebanon April 2017.
  • Qutaibah Althebyan, Hassan Najadat, Bushra AlZa’areer. “Performance Evaluation for Higher Educational Institutions within Data Envelopment Analysis”. In Proceedings of The 5th International Conference on E-Learning and E-Technologies in Education (ICEEE2016), Malaysia September 6 – 8, 2016, pp:37 – 43.
  • Qutaibah Althebyan, Rami Mohawesh, Qussai Yaseen and Yaser Jararweh. “Mitigating Insider Threats in a Cloud Using a Knowledgebase Approach while Maintaining Data Availability”. In Proceedings of the 10th International Conference for Internet Technology and Secured Transactions (ICITST-2015), London, UK, December 2015, pp: 226 – 231.
  • Rami Mohawesh, Qutaibah Althebyan, Qussai Yaseen and Yaser Jararweh. “A Knowledge Base Insider Threat Prevention Model in a Cloud Data Center”. In the Proceedings of the 3rd  International IBM Cloud Academy Conference (ICA CON 2015), Budapest, Hungary, May 21 – 23, 2015.
  • Qutaibah Althebyan, Omar AlQudah, Yaser Jararweh, Qussai Yaseen “Evaluating Map Reduce Tasks Scheduling Algorithms over Virtualized Infrastructure”. In the Proceedings of the 2nd International IBM Cloud Academy Conference (ICA CON 2014), Atlanta, Georgia USA, May 8 – 9, 2014.
  • Mahmoud Al-Ayyoub, Mustafa Daraghmeh, Yaser Jararweh and Qutaibah Althebyan. “Multi-Agent Based Dynamic Resource Provisioning and Monitoring In Cloud Computing Systems”. In the Proceedings of the 2nd International IBM Cloud Academy Conference (ICA CON 2014), Atlanta, Georgia USA, May 8 – 9, 2014.
  • Qutaibah Althebyan, Omar AlQudah, Yaser Jararweh, Qussai Yaseen “Multi-Threading Based Map Reduce Tasks Scheduling”. In the Proceedings of the 5th International Conference on Information and Communication Systems (ICICS 2014), April, 2014, Jordan.
  • Qussai Yaseen, Qutaibah Althebyan, Yaser Jararweh, “PEP-Side Caching: An Insider Threat Port”. The 14th IEEE International Conference on Information Reuse and Integration (IRI 2013) San Francisco, California, USA,  August, 2013.
  • Raed Shatnawi, Qutaibah Althebyan, Baraq Ghalib, Mohammad Molaji “Building A Smart Academic Advising System using Association Rule Mining”, 4th International Conference on Information and Communication Systems (ICICS 2013), Jordan, 2013.
  • Nahla Shatnawi, Qutaibah Althebyan, Wail Mardini. “Detection of Insiders Misuse in Database Systems” The International MultiConference of Engineers and Computer Scientists (IME, Mar 2011), Hong Kong, March 2011.
  • Qutaibah Althebyan, Brajendra Panda. “Performance Analysis of an Insider Threat Mitigation Model”. In Proceedings of the 3rd International Conference on Digital Management (ICDIM 2008). University of East London, London UK, 2008.
  • Qutaibah Althebyan, Brajendra Panda. “A Knowledge-Based Bayesian Model for Analyzing a System after an Insider Attack”. In Proceedings of the 23rd IFIP International Information Security Conference (SEC 2008), Milan, Italy, September 8-10, 2008.[Acceptance Rate = 28%]
  • Qutaibah Althebyan, Brajendra Panda. “Knowledge Extraction and Management for Insider Threat Mitigation”. In Proceedings of the 6th International Workshop on Security in Information Systems (WOSIS 2008), In Conjunction with ICEIS 2008, Barcelona, Spain, June 12-13, 2008.
  • Qutaibah Althebyan, Brajendra Panda. “A Knowledge-Base Model for Insider Threat Prediction”. In Proceedings of the 2007 IEEE Workshop on Information Assurance (IAW’07). United States Military Academy, West Point, New York, June 20-22, 2007.

Professional Experience

  • April 2018 – Present: Dean of College of Engineering Al Ain University, UAE
  • Sept. 2015 – Sept. 2016: Chairman of Software Engineering Department, Jordan University of Science and Technology, Jordan
  • Sept. 2011 – Sept. 2013: Chairman of Software Engineering Department, Jordan University of Science and Technology, Jordan
  • June. 2016 – Jan. 2018: Associate Professor, Software Engineering Department, Jordan University of Science and Technology, Jordan
  • Sept. 2009 – Feb. 2017: Assistant Professor, Software Engineering Department, Jordan University of Science and Technology, Jordan                            
  • Aug. 2008 – Sept. 2009: Assistant Professor, Computer Information Systems Department, Jordan University of Science and Technology, Jordan
  • Jan. 2010 – Jan. 2012: Adjunct Professor, New York Institute of Technology (NYiT) – Amman Campus, Jordan                            
  • Aug. 2004 – Aug. 2008: Research Assistant, Computer Science and Computer Engineering, University of Arkansas - Fayetteville, USA                                            
  • Aug. 2001 – May. 2003: Lab Proctor, Computer Science Department, University of Michigan – Dearborn, USA                                                     

Teaching Courses

Analytics Data Science – Master Level Course, Introduction to Programming, Discrete Structures, Design and Analysis of Algorithms, Security of Information Systems, Multimedia, Capstone, Capstone II

 

Visual Basic Programming, Introduction to Web Design, Operations Research, Information Security, Business Data Communications and Networks, Software Engineering Fundamentals, Software Modeling, Requirements Engineering, Software Security, Graduation Project I, Graduation Project II, Field Training

 

System Analysis and Design, Decision Support Systems, Cryptography

Memberships

IEEE

Conference Paper

A knowledge-base model for insider threat prediction

Published in: A knowledge-base model for insider threat prediction

Jun 20, 2017

/ Qutaibah Althebyan Brajendra Panda

Many consider insider attacks to be more severe and devastating than outsider attacks. Many techniques exist for defending against outsider attacks. However, little work has been presented for defending insider attacks and threats. In this work, we presented a prediction technique for insider threats. Due to the nature of these kinds of attacks, we relied on some characteristics of the insiders and the decomposition of objects in the underlying system in developing our method.


Conference Paper Full-text Available

Multi-threading based map reduce tasks scheduling

Jan 04, 2014

/ Qutaibah Althebyan Omar ALQudah Yaser Jararweh Qussai Yaseen

Map Reduce is a parallel and a distributed computing framework used to process datasets that have large scale nature on a cluster. Due to the nature of data that needs to be handled in the Map Reduce problem which involves huge amount of data, many problems came up that are of great importance. Scheduling tasks is considered one of these major problems that face Map Reduce frameworks. In this paper, we tackled this problem and proposed a new scheduling algorithm that is based on a multi-threading principle. In our proposed algorithm, we divided the cluster into multi blocks where each one of them is scheduled by a special thread. Two major factors are used to test our algorithm; the simulation time and the energy consumption. Our proposed scheduler is then compared with existing schedulers and the results showed the superiority and the preference of our proposed scheduler over the existing …