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.

1. 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
2. Rodriguez, David & Krishnan, Ram. (2023). Learnable Image Transformations for Privacy Enhanced Deep Neural Networks. 64-73. DOI:10.1109/TPS-ISA58951.2023.00018
3. 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