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Title: Logic Locking over TFHE for Securing User Data and Algorithms
Authors: Suemitsu, Kohei
Matsuoka, Kotaro
Sato, Takashi  kyouindb  KAKEN_id  orcid (unconfirmed)
Hashimoto, Masanori
Author's alias: 松岡, 航太郎
佐藤, 高史
橋本, 昌宜
Issue Date: 2024
Publisher: IEEE
Journal title: 2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC)
Start page: 600
End page: 605
Abstract: This paper proposes the application of logic locking over TFHE to protect both user data and algorithms, such as input user data and models in machine learning inference applications. With the proposed secure computation protocol algorithm evaluation can be performed distributively on honest-but-curious user computers while keeping the algorithm secure. To achieve this, we combine conventional logic locking for untrusted foundries with TFHE to enable secure computation. By encrypting the logic locking key using TFHE, the key is secured with the degree of TFHE. We implemented the proposed secure protocols for combinational logic neural networks and decision trees using LUT-based obfuscation. Regarding the security analysis, we subjected them to the SAT attack and evaluated their resistance based on the execution time. We successfully configured the proposed secure protocol to be resistant to the SAT attack in all machine learning benchmarks. Also, the experimental result shows that the proposed secure computation involved almost no TFHE runtime overhead in a test case with thousands of gates.
Description: 2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC), January 22-25, 2024, Incheon, Republic of Korea
Rights: © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
DOI(Published Version): 10.1109/ASP-DAC58780.2024.10473831
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