Late Breaking Results: COPPER: Computation Obfuscation by Producing Permutations for Encoding Randomly

被引：0

作者：

Hutto, Kevin ^{[2
]}

Mooney, Vincent ^{[1
,2
]}

机构：

[1] Georgia Inst Technol, Sch Comp Sci, Atlanta, GA 30332 USA

[2] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA

来源：

2023 60TH ACM/IEEE DESIGN AUTOMATION CONFERENCE, DAC | 2023年

关键词：

hardware security; encrypted computations; embedded systems;

D O I：

10.1109/DAC56929.2023.10247703

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Deployed embedded devices face security risks due to increased ease of physical access to the devices by unauthorized users. Capable adversaries can intercept a device to recover the data in memory, including results of performed sensitive computations. Device owners require data confidentiality on their physically insecure devices. To satisfy this goal we implement a novel method, COPPER (Computation Obfuscation by Producing Permutations for Encoding Randomly), to create data which never exists on the device digitally in plaintext format and which is subsequently used for computation. In this paper we utilize COPPER to calculate a moving average computation on encoded data.(1)

引用

页数：2