Burak Kantarci is an Associate Professor and the Founding Director of the Next Generation Communications and Computing Networks (NEXTCON) Research Lab and the Smart Connected Vehicles Innovation Centre (SCVI) at the University of Ottawa. Dr. Kantarci holds a Ph.D in computer engineering; and he is a globally recognized researcher particularly in mobile cloud computing, mobile crowd-sensing and AI-driven solutions for secure and trustworthy cyberspace. Dr. Kantarci is the co-author of over 200 publications in established journals and conferences, and 13 book chapters. He is well known for his contributions to the quantification of data trustworthiness in mobile crowd-sensing (MCS) systems, and game theoretic incentives to promote user participation in MCS campaigns with high value data; as well as AI-backed access control, authentication and machine learning-backed intrusion detection solutions in sensing environments. Dr. Kantarci served as the Chair of IEEE Communications Systems Integration and Modeling Technical Committee, and has served as the Technical Program Co-Chair/ Symposium Co-chair of more than twenty international conferences/ symposia/ workshops including IEEE Global Communications Conference (GLOBECOM) – Communications Systems QoS, Reliability and Modeling (CQRM) symposium. An Editor of the IEEE Communications Surveys and Tutorials, IEEE Internet of Things, Elsevier Vehicular Communications, an associate editor for IEEE Networking Letters, an area editor for IEEE Transactions on Green Communications and Networking, and an associate editor for IEEE Access. Dr. Kantarci is a Distinguished Speaker of the Association for Computing Machinery (ACM), senior member of ACM, and senior member of the IEEE.
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AI-Backed Security and Resilience for Cyber-Physical Systems
As Internet of Things systems become widely adopted, cyber-physical systems offer smarter environments and services than earlier networked systems by leveraging and integrating sensed data from...
Empowering behaviometrics for authentication
Learning unique behavioral patterns of an individual can improve detection of identity spoofing while addressing user comfort issues in user authentication processes. To this end, social and...
Trustworthiness and truthfulness issues in big crowd-sensed data
As a cloud-inspired sensing service model, mobile crowd-sensing can enable access to the Internet of Things (IoT)-based services. When mobile crowd-sensing becomes widely adopted, sensed data from...
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