Protection Research

The protection research team is developing innovative protection mechanisms and demonstrations for cloud computing, including access control, private computing, and protected computing technologies. Specific problems are under investigation within explicitly defined cloud security research contexts, encompassing security and privacy requirements, delivery models, deployment models, cloud actors, and attack techniques. Synergy with the detection, policy, and education and outreach teams is being pursued.

Recent Publications

  • Rodriguez, David & Krishnan, Ram. (2023). A Cycle-GAN Based Image Encoding Scheme for Privacy Enhanced Deep Neural Networks. 178-196. DOI: 10.1007/978-3-031-49099-6_11
  • Rodriguez, David & Krishnan, Ram. (2023). Learnable Image Transformations for Privacy Enhanced Deep Neural Networks. 64-73. DOI: 10.1109/TPS-ISA58951.2023.00018
  • P. Chhetri, S. Bhatt, P. Bhatt, M. Nur Nobi, J.Benson and R. Krishnan. Environment Aware Deep Learning Based Access Control Model. ACM Workshop on Secure and Trustworthy Cyber-Physical Systems, June 21, 2024. DOI: 10.1145/3643650.3659105
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Detection Research

The detection research team is developing system and host monitoring techniques and demonstrations to detect anomalous activity in a cloud along with digital forensics techniques for cloud-based systems. Specific problems are under investigation within explicitly defined cloud security research contexts, encompassing security and privacy requirements, delivery models, deployment models, cloud actors, and attack techniques. Synergy with the protection, policy, and education and outreach teams is being pursued.

Recent Publications

  • Aguilar D L, Perez M A M, Loyola-Gonzalez O, Choo K-K R and Bucheli-Susarrey. Towards an interpretable autoencoder: A decision tree-based autoencoder and its application in anomaly detection. IEEE Transactions on Dependable and Secure Computing [Early Access], Feb 2022. DOI: TDSC.2022.3148331
  • Richard Alvarez, Paras Bhatt, Đorđe Klisura, and Kim-Kwang Raymond Choo. (2024). Predicting Game Cheating Behavior Through the Social Network. In Proceedings of The 15th Dewald Roode Workshop on Information Systems Security Research (DRW 2023), 22-23 June 2023, Glasgow, Scotland.
  • Rasheed, Amar & Baza, Mohamed & Badr, Mahmoud & Alshahrani, Hani & Choo, Kim-Kwang. (2023). Efficient Crypto Engine for Authenticated Encryption, Data Traceability, and Replay Attack Detection Over CAN Bus Network. IEEE Transactions on Network Science and Engineering. PP. 1-17. DOI: 10.1109/TNSE.2023.3312545
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Policy Research

The policy research team is developing policy specification, composition, and verification techniques and demonstrations for secure cloud computing. Specific problems are under investigation within explicitly defined cloud security research contexts, encompassing security and privacy requirements, delivery models, deployment models, cloud actors, and attack techniques. Synergy with the protection, detection, and education and outreach teams is being pursued.

Recent Publications

  • Wang, Xiaoyin & Rafi, Tahmid & Meng, Na. (2023). VRGuide: Efficient Testing of Virtual Reality Scenes via Dynamic Cut Coverage. 951-962. DOI: 10.1109/ASE56229.2023.00197
  • Morales, G.; Romit, F.; Bienek-Parrish, A.; Jenkins, P. and Slavin, R. (2024). IoT Device Classification Using Link-Level Features for Traditional Machine Learning and Large Language Models. In Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP; ISBN 978-989-758-683-5; ISSN 2184-4356, SciTePress, pages 297-308. DOI: 10.5220/0012365700003648
  • Wang, Zhiwei & Xu, Jingye & Zhang, Jianqiu & Slavin, Rocky & Zhu, Dakai. (2024). An intelligent assistive driving solution based on smartphone for power wheelchair mobility. Journal of Systems Architecture. 149. DOI: 10.1016/j.sysarc.2024.103105
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Education and Outreach

The Education and Outreach team is conducting research on approaches to increase participation of underrepresented groups in high-tech computing, and developing mechanisms and protocols that can make these changes sustainable and extended to broader contexts. The fast growth of cloud computing and its diffusion into our everyday lives calls for different members of society, such as high school students, educators, industry practitioners, and academic researchers, to critically engage in purposeful collaborative opportunities, leading to new ideas and perspectives on secure cloud computing. The team is pursuing a multi-agent approach designed to provide numerous opportunities for such interactions. Synergy with the protection, detection, and policy teams is being pursued.

Recent Publications

  • Vargas-Alejo, V., Montero-Moguel, L. & Carmona, G. Interpretaciones de un docente durante un curso basado en la modelación. Perspectivas actuales de la Educación Matemática. SOMIDEM Editorial. (pp. 411-420) 2024. DOI: 10.24844/SOMIDEM/S3/2024/01-49
  • Montero-Moguel, L., Vargas-Alejo, V., Carmona, G. & Méndez-Huerta, D. Model eliciting activities as a powerful tool to expand collaborative work opportunities for undergraduate students. (2023). In T. Lamberg, & D. Moss, (Eds.) Proceedings of the forty-fifth annual meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education (Vol. 2), (pp. 168-177). University of Nevada, Reno. Oct 1 - 4, 2023.
  • Montero-Moguel, L., Mejia, J.A., & Carmona, G. Leveraging mathematical modeling to expand measurement process opportunities for engineering students. 2024 American Society for Engineering Education (ASEE) Annual Conference. Portland, Oregon, United States. June 23-26 2024.
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Multi-Cloud Laboratory

The Center-wide Multi-Cloud Laboratory (MCL) supports C-SPECC’s research and education activities, using dedicated hardware situated in UTSA’s Research Data Center, which provides professionally managed space, power, air conditioning, and Internet connectivity. The MCL operates multiple instances of the open-source, and free, OpenStack cloud platform, for research and education purposes. C-SPECC technical staff manage and assist in provisioning systems, and provide technical and research advice and support to researchers, and C-SPECC teams.

 

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Evaluation

Two overarching goals drive the C-SPECC evaluation process:

  1. To ensure that the Center’s plan is being followed (e.g., monitoring, compliance).
  2. To assess the quality of the activities, products, and outcomes.

Monitoring questions focus on what was accomplished during the grant. Evaluation questions assess the value of the grant activities, products, and outcomes.

Dr. Kurt Steuck of Steuck & Associates is the external evaluator for C-SPECC.

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Administration

C-SPECC is administratively a unit within the Institute for Cyber Security. Suzanne Tanaka is the Program Manager for both.

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Steering Committee

The Steering Committee consists of the C-SPECC Director, Co-PIs, and Team Leads. It monitors progress with respect to internal metrics, evaluation results, and external feedback.

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