Software heterogeneity technology based on application address randomization during software runtime

Chuan He; Bo Zhang; Zhuo Lv; Cen Chen; Hao Chang; Zesheng Xi; Yunfan Wang

doi:10.1117/12.3055759

9 January 2025 Software heterogeneity technology based on application address randomization during software runtime

Chuan He, Bo Zhang, Zhuo Lv, Cen Chen, Hao Chang, Zesheng Xi, Yunfan Wang

Author Affiliations +

Proceedings Volume 13486, Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024); 1348617 (2025) https://doi.org/10.1117/12.3055759
Event: Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024), 2024, Chengdu, China

Abstract

This article focuses on key endogenous security technologies and, based on the network endogenous security defense concept of "structure determines security" in mimetic defense, studies heterogeneous redundancy construction and heterogeneous technology and redundant execution technology for IoT access gateways. Firstly, the sources of heterogeneity were analyzed. Based on the timing of introducing heterogeneity, heterogeneous technologies were divided into three types: compile time, pre runtime, and runtime, and each of the three heterogeneous technologies was studied separately; We conducted in-depth research on process level heterogeneous redundant execution technology, namely multi variant execution. In order to solve several problems of process level redundant execution, we studied resource isolation technology on the Linux platform and combined it with container technology to form a container level redundant execution technology solution for power IoT access gateways.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chuan He, Bo Zhang, Zhuo Lv, Cen Chen, Hao Chang, Zesheng Xi, and Yunfan Wang "Software heterogeneity technology based on application address randomization during software runtime", Proc. SPIE 13486, Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024), 1348617 (9 January 2025); https://doi.org/10.1117/12.3055759

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