Thanh-Tung Le

Ph.D. candidate at Virginia Tech
tungle@vt.edu | | | | CV

I am a Ph.D. candidate in the Department of Computer Science at Virginia Tech, advised by Dr. Thang Hoang. Before starting my Ph.D., I was an FPGA Engineer developing 5G Physical Layer at Viettel High Technology Industries Corporation. I completed my B.Sc. degree in Computer Engineering from Hanoi University of Science and Technology.

My Ph.D. research has centered on Applied Cryptography, Security, and Privacy, with a primary focus on Searchable Encryption (SE), Multiparty Computation (MPC), Oblivious RAM (ORAM), and Proof of Retrievability (PoR). I am also interested in designing hardware accelerators using FPGA and GPU technologies, particularly for applications in Cryptography and AI/ML.


Recent News

    03/12/25: I will join Meta as a Ph.D. Software Engineer Intern in Summer 2025!
    03/10/25: Our paper “Hermes: Efficient and Secure Multi-Writer Encrypted Database” was accepted to IEEE S&P (Oakland) 2025!
    12/17/24: I passed the Ph.D. Preliminary Exam! [slides]

Projects

MUSES

Efficient Multi-User Searchable Encrypted Database.
A multi-server searchable encrypted system with multi-writer support. It hides all statistical information including search, result and volume patterns while achieving a minimal user overhead for keyword search and key rotation. My artifact has been awarded all three badges (available, functional, reproducible) in USENIX Security 2024.

Porla

Efficient Dynamic Proof of Retrievability for Cold Storage.
A proof of retrievability protocol that minimizes audit cost in terms of audit bandwidth and server/client computation. To achieve this, Porla utilizes incrementally constructible code, which is a type of error-correcting code, and verifiable computation techniques including Bulletproofs and KZG.

Hermes

Efficient and Secure Multi-Writer Encrypted Database.
A multi-writer searchable encrypted database that can prevent keyword-guessing attacks, achieve optimal search complexity (sublinear in the keyword set size), and forward privacy with user efficiency.

MAPLE

Metadata-Hiding Policy-Controllable Encrypted Search Platform with Minimal Trust.
A multi-server searchable encryption design attaining a high level of security. It protects search, result and volume patterns with malicious security, supports multiple users, also optimizes server computation complexity.

FPGA/Embedded System Design

Digital Signal Processing and Image Processing on FPGA.
An IP core for Digital Detail Enhancement algorithm that can enhance the quality of infrared images. The algorithm includes multiple stages of convolutions and computations based on the histogram of the input image.

Publications

Hermes: Efficient and Secure Multi-Writer Encrypted Database [paper] [code] [slides]
Tung Le, and Thang Hoang
IEEE Symposium on Security and Privacy (IEEE S&P) 2025

MUSES: Efficient Multi-User Searchable Encrypted Database [paper] [code] [slides]
Tung Le, Rouzbeh Behnia, Jorge Guajardo, and Thang Hoang
USENIX Security Symposium (USENIX Security) 2024

MAPLE: A Metadata-Hiding Policy-Controllable Encrypted Search Platform with Minimal Trust [paper] [code] [slides]
Tung Le, and Thang Hoang
Privacy Enhancing Technologies Symposium (PETS) 2023

Efficient Dynamic Proof of Retrievability for Cold Storage [paper] [code] [slides]
Tung Le, Pengzhi Huang, Attila A. Yavuz, Elaine Shi, and Thang Hoang
Annual Network and Distributed System Security Symposium (NDSS) 2023

Implement Detail Enhancement Algorithm on FPGA for Real-Time and Energy-Efficient Embedded Systems [paper] [slides]
Le Thanh Tung, Le Thanh Bang, Pham Trong Thuy, Nguyen Duc Hoan, and Vuong Dang Huy
IEEE International Conference on Communications and Electronics (IEEE ICCE) 2020


Teaching Assistant

CS5594: Blockchain Technologies (Graduate Level)
Spring 2024 (53 students)

CS5584: Network Security (Graduate Level)
Fall 2023 (46 students)

CS1044: Introduction to Programming in C (Undergraduate Level)
Spring 2022 (69 students)

CS3114: Data Structures and Algorithms (Undergraduate Level)
Fall 2021 (414 students), Fall 2024 (481 students)