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Gokhan Kul, Ph.D. |
Attention
I'm always looking for motivated Ph.D. students. I do not currently have any immediate openings but it may be helpful to start discussing interests.
If you are interested in working with me for your master's thesis or project, please contact me as soon as possible.
Recent News
- July 2024: Our supplement proposal on our SFS funding, titled "Building Blocks of Microprocessors: Simulations, Labs and Citizen Science for Inclusive STEM Learning" got funded ($241k) for one year by NSF. I serve as the Leading PI for this supplement.
- June 2024: Our proposal titled "Resilience Engineering of Machine Learning-enabled Open World Recognition" got funded ($247k) for another year by The U.S. Department of the Army, bringing total funding for this project to $546k over 3 years.
November 2023: I have been appointed as the VLDB Reproducibility Co-Chair.
July 2023: Our proposal titled "Resilience Engineering of Machine Learning-enabled Open World Recognition" got funded ($148k) for another year by The U.S. Department of the Army. I serve as the Principle Investigator.
December 2022: Our proposal titled "Accelerating Cybersecurity Education, Scholarship and Service" got funded by the National Science Foundation! I am proud to serve as a co-PI of this award.
August 2022: Our proposal titled "Resilience Engineering of Machine Learning-enabled Open World Recognition" got funded ($149,903) by The U.S. Department of the Army. I serve as the Principle Investigator (PI) in this project, and Dr. Lance Fiondella serves as the co-PI.
August 2022: UMass Dartmouth team's proposal titled "Intelligent Industrial Robotics and Cyber Security Test Bed" got funded ($500,000) by Massachusetts 2023 Skills Capital Grant Program. I am proud to be serving as a co-PI (co-Principal Investigator) in this team.
Education
Ph.D., Computer Science, University at Buffalo, SUNY (
),
June 2018M.S., Computer Engineering, METU (
),
August 2012B.A., Business Administration, Anadolu University (
),
May 2012B.S., Computer Engineering, TOBB University of Economics and Technology (
),
August 2010
Teaching
CIS552 Database Design, Instructor, University of Massachusetts Dartmouth, Spring 2021, Spring 2022, Fall 2024
CIS273 Computer Organization and Design, Instructor, University of Massachusetts Dartmouth, Spring 2022, Spring 2023, Spring 2024, Spring 2025
CIS272 Introduction to Computer Systems, Instructor, University of Massachusetts Dartmouth, Fall 2021, Fall 2022, Fall 2023
CIS442/542 Digital Forensics, Instructor, University of Massachusetts Dartmouth, Fall 2019, Fall 2020, Fall 2021, Fall 2022, Fall 2023, Fall 2024, Fall 2025
CIS444/602 Cyber Defense and Operations, Instructor, University of Massachusetts Dartmouth, Spring 2021, Spring 2023, Spring 2025
Publications
Journal Papers
Zakaria Faddi, Karen da Mata, Priscila Silva, Vidhyashree Nagaraju, Susmita Ghosh, Gokhan Kul, Lance Fiondella. 2024. Quantitative assessment of machine learning reliability and resilience. Journal of Risk Analysis. Wiley. Volume TBD. Issue TBD. July 2024.
Chidera Biringa and Gokhan Kul. 2023. PACE: A Program Analysis Framework for Continuous Performance Prediction. ACM Transactions on Software Engineering and Methodology (ACM TOSEM).Volume TBD, Issue TBD, December 2023
Gokhan Kul, Shambhu Upadhyaya and Andrew Hughes. 2021. An Analysis of Complexity of Insider Attacks to Databases. ACM Transactions on Management Information Systems.Volume 12, Issue 1, March 2021
Akash Sundararaj and Gokhan Kul. 2021. Impact Analysis of Training Data Characteristics for Phishing Email Classification. Journal of Mobile Networks, Ubiquitous Computing, and Dependable Applications (JoWUA). 12(2), 85-98
Heather Craddock, Lakshmi Prasanna Konudula and Gokhan Kul. 2019. A Survey on the Challenges of Implementing Physical Memory Pools. Journal of Internet Systems and Information Security. (JISIS).
Gokhan Kul, Duc Luong, Ting Xie, Varun Chandola, Oliver Kennedy, Shambhu Upadhyaya. 2018. Similarity Measures for SQL Query Clustering. IEEE Transactions on Data Engineering (TKDE).
Gokhan Kul and Shambhu Upadhyaya. 2016. Towards Cyber Ontology for Insider Threats in the Financial Sector. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (JoWUA). 6(4), 64-85
Gokhan Kul, Tansel Ozyer, Bulent Tavli. 2014. IEEE 802.11 WLAN based Real Time Indoor Positioning: Literature Survey and Experimental Investigations. Procedia Computer Science, 34, 157-164, ISSN 1877-0509, DOI=10.1016/j.procs.2014.07.078
Conference Papers
Gaspard Baye, Priscila Silva, Alexandre Broggi, Lance Fiondella, Nathaniel Bastian and Gokhan Kul. 2023. Performance Analysis of Deep-Learning Based Open Set Recognition Algorithms for Network Intrusion Detection Systems. In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS). Miami, FL
Kevin Montambault, Gokhan Kul. 2023. Image Attribute Estimation for Forensic Image Reconstruction from Fragments. In Proceedings of the 56th Hawaii International Conference on System Sciences (HICSS'23), Maui, Hawaii
Julia Sorrentino, Priscila Silva, Gaspard Baye, Gokhan Kul and Lance Fiondella. 2022. Covariate Software Vulnerability Discovery Model to Support Cybersecurity Test and Evaluation. In Proceedings of the 33rd IEEE International Symposium on Software Reliability, Charlotte, NC
Chidera Biringa, Gaspard Baye, and Gokhan Kul. 2022. Short Paper: Static and Microarchitectural ML-Based Approaches For Detecting Spectre Vulnerabilities and Attacks. In Proceedings of Hardware and Architectural Support for Security and Privacy, Chicago, IL
Jack D'Agostino and Gokhan Kul. 2021. Toward Pinpointing Data Leakage from Advanced Persistent Threats. In Proceedings of the IEEE International Conference on Intelligent Data Security, New York, NY
Chidera Biringa and Gokhan Kul. 2021. Automated User Experience Testing through Multi-Dimensional Performance Impact Analysis. In Proceedings of the IEEE/ACM International Conference on Automation of Software Test (AST 2021), Online.
Prinkle Sharma, Umesh Siddanagaiah and Gokhan Kul. 2020. Towards an AI-Based After-Collision Forensic Analysis Protocol for Autonomous Vehicles. In the Proceedings of the IEEE Internationa Conference on Security and Privacy - IEEE Workshop on Assured Autonomous Systems (IEEE WAAS 2020)
Heather Craddock, Lakshmi Prasanna Konudula, Kun Cheng and Gokhan Kul. 2019. The Case for Physical Memory Pools: A Vision Paper. In Proceedings of the International Conference on Cloud Computing (CLOUD 2019), San Diego, CA
Gokhan Kul, Shambhu Upadhyaya and Varun Chandola. 2018. Detecting Data Leakage from Databases on Android Apps with Concept Drift. In Proceedings of the 17th IEEE International Conference On Trust, Security and Privacy in Computing and Communications (IEEE TrustCom 18), New York, NY
Gokhan Kul, Shambhu Upadhyaya and Andrew Hughes. 2017. Complexity of Insider Attacks to Databases. In Proceedings of the 9th ACM CCS International Workshop on Managing Insider Security Threats (MIST ’17), Dallas, TX
Vishal Sharma, Ilsun You and Gokhan Kul. 2017. Socializing Drones for Inter-Service Operability in Ultra-Dense Wireless Networks using Blockchain. In Proceedings of the 9th ACM CCS International Workshop on Managing Insider Security Threats (MIST ’17), Dallas, TX
Gokhan Kul, Duc Luong, Ting Xie, Patrick Coonan, Varun Chandola, Oliver Kennedy and Shambhu Upadhyaya. 2016. Ettu: Analyzing Query Intents in Corporate Databases. In Proceedings of the 25th International Conference Companion on World Wide Web (WWW ’16 Companion). International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland, 463-466. DOI: 10.1145/2872518.2888608
Gokhan Kul and Shambhu Upadhyaya. 2015. A Preliminary Cyber Ontology for Insider Threats in the Financial Sector. In Proceedings of the 7th ACM CCS International Workshop on Managing Insider Security Threats (MIST ’15). ACM, New York, NY, USA, 75–78. DOI=10.1145/2808783.2808793
Deniz Iren, Gokhan Kul, and Semih Bilgen. 2014. Utilization of synergetic human-machine clouds: a big data cleaning case. In Proceedings of the 1st International Workshop on CrowdSourcing in Software Engineering (CSI–SE 2014). ACM, New York, NY, USA, 15–18. DOI=10.1145/2593728.2593733
Deniz Iren, Gokhan Kul, and Semih Bilgen. 2014. İnsan ve Makine Bulutları Sinerjisi: Kitle Kaynaklı Çalışma ile Veri Temizleme Örnek Uygulaması. In Proceedings of the 8th Turkish National Software Engineering Symposium 2014 (UYMS 2014). CEUR–WS, Germany, Vol–1221, 2014, Pages 571–579.
Poster Presentations
Gokhan Kul. 2017. Database Access Monitoring. Traffic and Monitoring Analysis Conference, Dublin, Ireland, June 2017
Gokhan Kul. 2012. Crowdsourcing Ontology Design. 4th EURO-NF Summer School for Master and PhD Students on Modelling and Analysis of Novel Mechanisms and Future Internet Applications, University of Wuerzburg, Germany, April 2012
Project Reports
Gokhan Kul, Duc Luong, Ting Xie, Patrick Coonan, Varun Chandola, Oliver Kennedy and Shambhu Upadhyaya. 2016. Summarizing Large Query Logs in Ettu. eprint arXiv:1608.01013
Gokhan Kul, Y. Deniz Iren, Ezgi Akkaya, Engin Bozkurt, Eylem Elif Mavis. 2014. Integration of DSpace with Computing Center Services. Open Repositories 2014, Helsinki, Finland, June 2014 (Withdrawn after acceptance due to visa problem)
Professional Activities
Reproducibility Committee Co-Chair for VLDB 2023-Current
Program Committee Member for ICWSM 2021, 2022, 2023, 2024 Atlanta, GA.
Reproducibility Committee Member for VLDB 2018-2022
Program Committee Member for SecureComm 2019, 2020
Program Committee Member for ICPADS 2019
External Reviewer for VLDB 2018, Rio De Janeiro, Brazil
Reproducibility Committee Member for SIGMOD 2016-2017
Program Committee Member for ACM CCS MIST 2016-2017
Shadow Program Committee Member for IEEE Security and Privacy 2017
Reviewer for ACM Computing Reviews, December 2014 - Present
Software
EttuBench SQL Query clustering quality evaluation tool
WifiStrength, an Android application to track signal strengths of access points visible
DSpace 4.1, a very useful institutional repository system that I programmed plugins specialized for the needs of my previous institution.
Datasets
UB Exam Dataset, is a dataset that contains SQL queries which students wrote as an answer and corresponding grades of 2 different questions asked at UB's graduate level Database Systems class in two consecutive years (Link should be active after the paper that includes the investigations of the dataset is submitted to EDBT 2017 conference).
Contact
gkul [at] umassd.edu