Confidentiality and Integrity Schemes for Multicore Shared Memory Systems

Author:

Yang Pengfei1,Lv Wenkai1,Huang Jiayang1,Wang Quan1,Huang Xiaokun1,Xie Kun1

Affiliation:

1. School of Computer Science and Technology, Xidian University, Xi’an, P. R. China

Abstract

In embedded multicore shared memory systems, processing elements (PEs) are mutually untrusted since they carry different computing tasks independently. Therefore, the sharing of secret constants (SCs) between PEs, which is applied in the existing confidentiality protection schemes, will lead to the leakage of nonshared data. Besides, for integrity protection, tree construction checking over the whole counter space leads to the increase of both memory occupation and the average delay of verification. In this paper, we propose a ciphertext sharing confidentiality protection scheme based on certificateless proxy re-encryption and an integrity protection scheme based on a multigranularity scalable hash tree for secure data sharing between untrusted processing elements (SDSUP). With our schemes, the SC does not need to be shared and the scale of the checking tree is reduced, thus solving the leakage of nonshared data and reducing the high cost in integrity check. The results from the Rice Simulator for ILP Multiprocessors (RSIM) multicore simulator show that compared with the unprotected system, the performance degradation from applying the confidentiality protection scheme is 17.3% on average. Moreover, the performance degradation of the integrity protection scheme is 12.89%, which is superior to 35.36% for the bonsai Merkle tree (BMT), 29.49% for the multigrained hash tree (MGT) and 21.82% for the multigranularity incremental hash tree (MIT).

Funder

National Natural Science Foundation of China

Shaanxi Key Technology R&D Program

Publisher

World Scientific Pub Co Pte Ltd

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Electrical and Electronic Engineering,Hardware and Architecture

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1. Caching Hybrid Rotation: A Memory Access Optimization Method for CNN on FPGA;Journal of Circuits, Systems and Computers;2023-03-04

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