Journal articles

1. Jeevan Devagiri, Sidike Paheding, Quamar Niyaz, Xiaoli Yang, and Samantha Smith, “Augmented Reality and Artificial Intelligence in Industry: Trends, Tools, and Future Challengers,” Elsevier Expert Systems with Applications, vol. 207, no. 118002, 2022. 

2. John Estrada, Sidike Paheding, Xiaoli Yang, and Quamar Niyaz, “Deep Learning Incorporated Augmented Reality Application for Engineering Lab Training”, MDPI Applied Sciences 12, no. 10: 5159, 2022. 

3. Yuchen Li, Jered Pawlak, Joshua Price, Khair Al Shamaileh, Quamar Niyaz, Sidike Paheding, and Vijay Devabhaktuni, “Jamming Detection and Classification in OFDM-based UAVs via Feature- and Spectrogram-tailored Machine Learning,” in IEEE Access, Vol. 10, pp. 16859-16870, 2022. 

4. Akshay Mathur, Laxmi Podilla, Keyur Kulkarni, Quamar Niyaz, and Ahmad Y Javaid, “NATICUSdroid: A Malware Detection System in Android using Native and Custom Permissions,” Elsevier Journal of Information Security and Applications, vol. 58, no. 102696, 2021. 

5. P. C. Srinivasa Rao, A. J. Sravan Kumar, Quamar Niyaz, Sidike Paheding, and Vijay Devabhaktuni, “A Chemical Reaction Optimization based Feature Selection Technique for Machine Learning Classification Problems,” Elsevier Expert Systems and Applications, vol. 167, no. 114169, 2021. 

6. Kyle Greene, Deven Rodgers, Henry Dykhuizen, Quamar Niyaz, Khair Al Shamaileh, and Vijay Devabhaktuni, “A Defense Mechanism Against Replay Attack in Remote Keyless Entry Systems Using Timestamping and XOR Logic,” IEEE Consumer Electronics Magazine, Vol. 10, Issue 1, pp. 101–108, 2021 (Invited submission from IEEE ICCE 2020).

7. Abel Reyes, Francisco Vaca, Gabriel Aguayo, Quamar Niyaz, and Vijay Devabhaktuni,“A Machine Learning based Two-stage Wi-Fi Network Intrusion Detection System,” MDPI Electronics, Vol. 9, Issue 10, 2020.

8. Farha Jahan, Weiqing Sun, Quamar Niyaz, and Mansoor Alam, “Security Modeling of Autonomous Systems: A Survey,” ACM Computing Surveys (CSUR), Vol. 52, Issue 5, pp.1–34, 2019.

9. Quamar Niyaz, Weiqing Sun, and Ahmad Y Javaid, “A Deep Learning Based DDoS Detection in Software Defined Networking (SDN),” EAI Endorsed Transactions on Security and Safety, Vol. 4, Issue 12, 2017.

10. Quamar Niyaz, Weiqing Sun, Ahmad Y Javaid, and Mansoor Alam, “A Deep Learning Approach for Network Intrusion Detection System,” In EAI Endorsed Transactions on Security and Safety, Vol. 3, Issue 9, 2016 (Invited paper from EAI BICT 2015).

Conference and Workshop Papers

1. Sai Sushmitha Sudha, Sai Suma Sudha, Ahmad Y. Javaid, Quamar Niyaz, Xiaoli Yang, "Examining the Impact of Early Cybersecurity Education in the Selection of Cybersecurity as a Career among High School Senior and University Freshmen Students," 2023 ASEE Annual Conference & Exposition, Baltimore, MD, USA, 2023.

2. Sai Suma Sudha, Sai Sushmitha Sudha, Ahmad Y. Javaid, Quamar Niyaz, and Xiaoli Yang, "Evaluating the Impact of a Multimodal Cybersecurity Education Approach on High School Student Cybersecurity Learning," 2023 ASEE Annual Conference & Exposition, Baltimore, MD, USA, 2023.

3. Rayed S. Ahmad, Asmer H. Ali, Syed M. Kazim, and Quamar Niyaz, "A GAF and CNN based Wi-Fi Network Intrusion Detection System," IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Hoboken, NJ, USA, 2023.

4. Sai Sushmitha Sudha, Jyothi Priyanka Bandreddi, Laxmi Mounika Podila, Ramesh Govindula, Austin Richardson, Quamar Niyaz, Xiaoli Yang, and Ahmad Javaid, "Impact of Smartphone-Based Interactive Learning Modules on Cybersecurity Learning at the High-School Level," 2023 IEEE Global Engineering Education Conference (EDUCON), Kuwait, Kuwait, 2023.

5. Sai Suma Sudha, Gabriel Castro Aguayo, Abel R Angulo, Jyothirmai Kothakapu, Quamar Niyaz, Xiaoli Yang, and Ahmad Y Javaid, "Changes in High-School Student Attitude and Perception Towards Cybersecurity Through the Use of an Interactive Animated Visualization Framework," 2023 IEEE Global Engineering Education Conference (EDUCON), Kuwait, Kuwait, 2023.

6. Xinrun Zhang, Akshay Mathur, Lei Zhao, Safia Rahmat, Quamar Niyaz, Ahmad Javaid, and Xiaoli Yang, “An Early Detection of Android Malware Using System Calls based Machine Learning Model,” 17th International Conference on Availability, Reliability and Security (ARES 2022), August 23-26, 2022, Vienna, Austria.

7. Abel Reyes, Xiaoli Yang, Quamar Niyaz, Sidike Paheding, and Ahmad Javaid, “A Secure Software Engineering Design Framework for Educational Purpose” 22nd IEEE Electro Information Technology (IEEE EIT), Mankato, Minnesota, USA, May 19–21, 2022.

8. Joshua Price, Yucehn Li, Khair Al Shamaileh, Quamar Niyaz, Naima Kaabouch, and Vijay Devabhaktuni, “Real-time Classification of Jamming Attacks against UAVs via on-board Software-defined Radio and Machine Learning-based Receiver Module” 22nd IEEE Electro Information Technology (IEEE EIT), Mankato, Minnesota, USA, May 19–21, 2022.

9. Jansen Tan, Divya Ravindra, Quamar Niyaz, Xiaoli Yang, Ahmad Y Javaid, and Sidike Paheding, “Mini-projects based Cybersecurity Modules for an Operating System Course using xv6,” 2022 ASEE Annual Conference and Exposition, Minneapolis, Minnesota, USA, June 26-29, 2022.

10. Jyothirmai Kothakapu, Ahmad Y Javaid, Quamar Niyaz, Xiaoli Yang, Sidike Paheding, and Charlene Czerniak, “Introducing Cybersecurity in a Discrete Structures Course Through a Visualization-based Plug-and-Play Cryptography Module,” 2022 ASEE Annual Conference and Exposition, Minneapolis, Minnesota, USA, June 26-29, 2022.

11. Akshay Mathur, Ethan Ewoldt, Quamar Niyaz, Xiaoli Yang, and Ahmad Javaid, “Permission Educator: App for Educating Users about Android Permissions,” at 13th International Conference on Intelligent Human-Computer Interaction, December 20-22, 2021, Kent, Ohio, USA.

12. Jered Pawlak, Yuchen Li, Joshua Price, Matthew Wright, Khair Al Shamaileh, Quamar Niyaz, and Vijay Devabhaktuni, “A Machine Learning Approach for Detecting and Classifying Jamming Attacks Against OFDM-based UAVs,” ACM Workshop on Wireless Security and Machine Learning (WiseML 2021), July 2, 2021, Abu Dhabi, UAE (Online). 

13. Laxmi M Podila, Jyothi Bandreddi, Javier Campos, Quamar Niyaz, Ahmad Y Javaid, and Xiaoli Yang, “Practice-oriented Smartphone Security Exercises for Developing Cybersecurity Mindset in High School Students,” IEEE Teaching, Assessment, and Learning in Engineering (TALE), Dec 8-11, 2020, Online.

14. Xinrun Zhang, Quamar Niyaz, Farha Jahan, and Weiqing Sun, “Early detection of Host based Intrusion Detection in Linux Environment,” 20th IEEE Electro Information Technology (IEEE EIT), July 31–Aug 1, 2020, Online.

15. Farha Jahan, Weiqing Sun, and Quamar Niyaz,“A Non-Cooperative Game based Model for the Cybersecurity of Autonomous Systems,” Proceedings of the Workshop on Assured Autonomous Systems (WAAS) co-located with the 41st IEEE Symposium on Security and Privacy, May 21, 2020, Online.

16. Abel A Reyes, Colin Elkin, Quamar Niyaz, Xiaoli Yang, Sidike Paheding, Vijay Devabhaktuni, “A Preliminary Work on Visualization-based Education Tool for High School Machine Learning Education,” IEEE Integrated STEM Education Conference (ISEC), Aug 1, 2020, Online.

17. Kyle Greene, Deven Rodgers, Henry Dykhuizen, Kyle McNeil, Quamar Niyaz, and Khair Al Shamaileh, “Timestamp-based Defense Mechanism Against Replay Attack in Remote Keyless Entry Systems,” 2020 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, USA, 2020.

18. Hafiz Mohammad Junaid Khan, Quamar Niyaz, Vijay Devabhaktuni, Sile Guo and Umair Shaikh, “Identifying Generic Features for Malicious URL Detection System,” IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York City, NY, USA, 2019.

19. Safia Rahmat, Quamar Niyaz, Akshay Mathur, Ahmad Javaid, and Weiqing Sun, “Network Traffic-Based Hybrid Malware Detection for Smartphone and Traditional Networked Systems,” IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York City, NY, USA, 2019.

20. Gabriel C Aguayo, Ulises Morales, Xiaoyu Long, Quamar Niyaz, Xiaoli Yang, and Ahmad Y. Javaid. “An Introductory Visualization Aid for Cybersecurity Education,” In Proceedings of the International Conference on Frontiers in Education: Computer Science and Computer Engineering (FECS), Las Vegas, NV, USA, 2019.

21. Medha Pujari, Jhaghapratha Narayanamoorthy, Weiqing Sun, Farha Jahan, Bill McCreary, Quamar Niyaz, and Vijay K Devabhaktuni, “PortableVN: A Generic Mobile Application for Network Security Testbeds,” In Proceedings of the International Conference on Security and Management (SAM), Las Vegas, NV, USA, 2019.

22. Francisco D Vaca and Quamar Niyaz, “An Ensemble Learning based Wi-Fi Network Intrusion Detection System (WNIDS),” 17th IEEE International Symposium on Network Computing and Applications (IEEE NCA), Cambridge, MA, USA, 2018.

23. Wei Liu, Quamar Niyaz, Weiqing Sun, and Ahmad Y Javaid,“A Web-based Lightweight Testbed for Supporting Network Security Hands-on Labs,” 18th IEEE Electro Information Technology (IEEE EIT), Rochester, Michigan, USA, 2018. 

24. Safia Rahmat, Quamar Niyaz, Ahmad Y Javaid, and Weiqing Sun “Normal and Anomalous Traffic Pattern Analysis for Organizational Networks”, 30th IEEE Canadian Conference on Electrical and Computer Engineering (IEEE CCECE) Windsor, Ontario, Canada, 2019.

25. Ahmad M Karimi, Quamar Niyaz, Weiqing Sun, Ahmad Y Javaid, and Vijay K Devabhaktuni, “Distributed Network Traffic Feature Extraction for a Real-time IDS,” 15th IEEE Electro Information Technology (IEEE EIT), Grand Forks, North Dakota, USA, 2016.

26. Quamar Niyaz, Weiqing Sun, Ahmad Y Javaid, and Mansoor Alam, “A Deep Learning Approach for Network Intrusion Detection System,” 9th EAI International Conference on Bio-inspired Information and Communications Technologies, New York, USA, 2015.

27. Quamar Niyaz, Weiqing Sun, Rao Xu, and Mansoor Alam, “LightVN: A Light-Weight Testbed for Network and Security Experiments,” International Conference on Information Technology: New Generations (IEEE ITNG), Las Vegas, NV, USA, 2015.

28. Quamar Niyaz, Weiqing Sun, and Mansoor Alam, “Impact on SDN Powered Network Services under Adversarial Attacks,” International Conference on Soft Computing and Software Engineering (SCSE’15), Berkeley, CA, 2015.

29. Junghwan Kim, Quamar Niyaz, and Ahmad Y Javaid, “Performance Evaluation of VoIP Broadcasting over LTE for varying Speeds and Distance of Mobile Nodes,” IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (IEEE BMSB), Beijing, China, 2014.

30. Arvind Mahla, Deepak Martin, Ishani Ahuja, Quamar Niyaz, and Aaditeshwar Seth, “Motivation and Design of a Content Distribution Architecture for Rural Areas,” In Proceedings of the 2nd ACM Symposium on Computing for Development (ACM DEV), Atlanta, Georgia, USA, 2012.

Peer-reviewed Poster Presentations

1. Xinrun Zhang, Akshay Mathur, Lei Zhao, Safia Rahmat, Quamar Niyaz, Ahmad Javaid, and Xiaoli Yang, “An Early Detection of Android Malware Using System Calls based Machine Learning Model,” The 29th Network and Distributed System Security Symposium (NDSS), Feb 27–March 3, 2023, San Diego, CA, USA.

2. Kenneth Guernsey, Jacob Tietz, Quamar Niyaz, Xiaoli Yang, Ahmad Y Javaid, and Sidike Paheding, “Work-In-Progress: Enabling Secure Programming in C++ & Java through Practice Oriented Modules,” at 2022 ASEE Annual Conference and Exposition, Minneapolis, Minnesota, USA, June 26-29, 2022.

3. Akshay Mathur, Laxmi Podilla, Keyur Kulkarni, Quamar Niyaz, and Ahmad Y Javaid, “NATICUSdroid: A Malware Detection System in Android using Native and Custom Permissions,” The 27th Network and Distributed System Security Symposium (NDSS), Feb 21–25, 2021, Online.

4. Javier Campos, Kristen Johnson, Jonathan Neeley, Staci Roesch, Farha Jahan, Quamar Niyaz, and Khair Al Shamaileh, “A Machine Learning based Smartphone App for GPS Spoofing Detection,” 16th EAI International Conference on Security and Privacy in Communication Networks (Securecomm 2020), October 21–23, 2020, Online.

Book Chapters

1. Safia Rahmat, Quamar Niyaz, Ahmad Y. Javaid, and Weiqing Sun, "Application of Deep Learning as a Pattern Recognition Technique in Information Security," In Advances in Pattern Recognition Research, Eds: Thomas Lu, Senior Researcher & Tien-Hsin Chao, Principal Researcher, NASA/JPL/Caltech, NOVA Science Publishers, ISBN: 978-1-53614-429-1.