Adrian Cartagena, Gerald Rimmer, Thomas Van Dalsen, Lanier Watkins, Avi Rubin and William H. Robinson, “Privacy Violating Opensource Intelligence Threat Evaluation Framework: A Security Assessment Framework for Critical Infrastructure Owners” The IEEE Computing and Communication Workshop and Conference (CCWC), January 2020.

Mandira Hegde, Gilles Kepnang, Mashaal Al Mazroei, Jeffrey S. Chavis, and Lanier Watkins, “Identification of Botnet Activity in IoT Network Traffic Using Machine Learning” To Appear in IEEE International Conference on Intelligent Data Science Technologies and Applications (IDSTA), October 2020.

Mandira Hegde, Ian McCulloh and John Piorkowski, “Examining Massive Open Online Course (MOOC) Superposter Behavior Using Social Network Analysis”  In Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019), August 2019.

Mohammed Rashed, John Piorkowski and Ian McCulloh, “Evaluation of Extremist Cohesion in a Darknet Forum Using ERGM and LDA” In Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019), August 2019.

Sharon Grubner, John Piorkowski and Ian McCulloh, “Social Media as a Main Source of Customer Feedback – Alternative to Customer Satisfaction Surveys” In Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019), August 2019.

Ryan Van Soelen and John Sheppard, “Using Winning Lottery Tickets in Transfer Learning for Convolutional Neural Networks,” Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), July 2019.

Rachel Cohen, Ian McCulloh and Richard Takacs, “Better Quality Classifiers for Social Media Content: Crowdsourcing with Decision Trees” In Proceedings 6th International Conference on Advanced Computing, Networking, and Informatics (ICACNI), June 2018.

Daniel Ladouceur, Bimmy Pujari, Edward Gleeck and Joel Coffman, “Techniques for Mutual Auditability in a Cloud Environment” Proceedings of the International Workshop on Cloud, IoT, and Fog Security (CIFS ‘19), December 2019.

Kelly Brady, Seung Moon, Tuan Nguyen, Joel Coffman, “Docker Container Security in Cloud Computing” Proceedings of the 10th Computing and Communication Workshop and Conference (CCWC), January 2020.

Muhammad Ayub, Patrick Knowles, Brandon Phan, and Joel Coffman, “The Cost of a Macaroon,” Proceedings of the 2020 IEEE Systems Security Symposium (SSS), April 2020.

Sumeet Shah and John Sheppard, “Evaluating Explanations of Convolutional Neural Network Classifications,” Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), July 2020.

Sanchay Gupta, Robert Miceli, and Joel Coffman, “A Replication Study to Explore Co-Residency of Virtual Machines in the Cloud,” Proceedings of the 2020 International Conference on Cloud Computing (CLOUD), August 2020.

Peter Cocoros, Matthew Sobocinski, Kyle Steiger, and Joel Coffman, “Evaluating Techniques for Practical Cloud-based Network Intrusion Detection,” Proceedings of the 5th IEEE International Conference on Smart Cloud (SmartCloud ’20), November 2020.

Shambavi Sadayappan, John Piorkowski and Ian McCulloh, “Evaluation Political Party Cohesion Using Exponential Random Graph Modeling” In Proceedings 2018 IEEE/ACM Conference on Advances in Social Network Analysis and Mining 2018 (ASONAM), August 2018.

Adam Reed, John Piorkowski, and Ian McCulloh, “Correlating NBA Team Network Centrality Measures with Game Performance” In Proceedings 2018 IEEE/ACM Conference on Advances in Social Network Analysis and Mining 2018 (ASONAM), August 2018.

Anthony Perez and Ebrima N. Ceesay, “Improving End-to-End Verifiable Voting Systems with Blockchain Technologies,” 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), July 2018.

Faculty Publications:

Jeffery Chavis, Anna Buczak, Lanier Watkins, and Avi Rubin, “Connected Home Automated Security Monitor (CHASM): Protecting IoT Through Application of Machine Learning” In IEEE Computing and Communication Workshop and Conference (CCWC), January 2020.