- Showkot Hossain, Wenyi Tang, Changhao Chenli, Haijian Sun, WenZhan Song, Seokki Lee, Mic Bowman, Taeho Jung
- “MtDB: A Decentralized Multi-Tenant Database for Secure Data Sharing”
- 8th IEEE International Conference on Blockchain (IEEE Blockchain 2025)
Tag: TEE
A paper is accepted by SN Computer Science
- Ryan Karl, Nirajan Koirala, Tasha Januszewicz, Jonathan Takeshita, Taeho Jung
- “Cryptonite: A Framework for Flexible Time-series Secure Aggregation with Non-interactive Fault Recovery”
- SN Computer Science
A paper accepted by IJIS
- Ryan Karl, Hannah Burchfield, Jonathan Takeshita, Taeho Jung
- “Developing Non-Interactive MPC with Trusted Hardware for Enhanced Security”
- International Journal of Information Security
A paper accepted by SecureComm 2021
- Jonathan Takeshita, Ryan Karl, Al-Amin Mohammed, Aaron Striegel, and Taeho Jung
- “Provably Secure Contact Tracing with Conditional Private Set Intersection”
- 17th EAI International Conference on Security and Privacy in Communication Networks (SecureComm), 2021
A paper accepted by SecureComm 2021
- Ryan Karl, Jonathan Takeshita, Al-Amin Mohammed, Aaron Striegel, and Taeho Jung
- “Cryptonomial: A Framework for Private Time-Series Polynomial Calculations”
- 17th EAI International Conference on Security and Privacy in Communication Networks (SecureComm), 2021
A paper accepted by SecureComm 2021
- Ryan Karl, Jonathan Takeshita, and Taeho Jung
- “Cryptonite: A Framework for Flexible Time-Series Secure Aggregation with Non-interactive Fault Recovery”
- 17th EAI International Conference on Security and Privacy in Communication Networks (SecureComm), 2021
A paper accepted by IEEE DCOSS 2021
- Ryan Karl, Jonathan Takeshita, Al-Amin Mohammed, Aaron Striegel
- “CryptoGram: Fast Private Calculations of Histograms over Multiple Users”
- IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS) 2021
A poster accepted by HotSos 2020
- Ryan Karl, Jonathan Takeshita, Taeho Jung
- “Using Intel SGX to Improve Private Neural Network Training and Inference”
- 7th Annual Hot Topics in the Science of Security (HoTSoS) Symposium, 2020
A Work-in-Progress paper accepted by HotSos 2020
- Ryan Karl, Jonathan Takeshita, Taeho Jung
- “WiP: Using Intel SGX to Improve Private Neural Network Training and Inference”
- 7th Annual Hot Topics in the Science of Security (HoTSoS) Symposium, 2020