Reconciling $$d+1$$ Masking in Hardware and Software

Abstract

The continually growing number of security-related autonomous devices requires efficient mechanisms to counteract low-cost side-channel analysis (SCA) attacks. Masking provides high resistance against SCA at an adjustable level of security. A high level of SCA resistance, however, goes hand in hand with an increasing demand for fresh randomness which drastically increases the implementation costs. Since hardware based masking schemes have other security requirements than software masking schemes, the research in these two fields has been conducted quite independently over the last ten years. One important practical difference is that recently published software schemes achieve a lower randomness footprint than hardware masking schemes. In this work we combine existing software and hardware masking schemes into a unified masking algorithm. We demonstrate how to protect software and hardware implementations using the same masking algorithm, and for lower randomness costs than the separate schemes. Especially for hardware implementations the randomness costs can in some cases be halved over the state of the art. Theoretical considerations as well as practical implementation results are then used for a comparison with existing schemes from different perspectives and at different levels of security.