Dynamic Information Flow Tracking: Taxonomy, Challenges, and Opportunities release_zfkiddrjvbfjli7ht6x5jgyp7q

by Kejun Chen, Xiaolong Guo, Qingxu Deng, Yier Jin

Published in Micromachines by MDPI AG.

2021   Volume 12, p898

Abstract

Dynamic information flow tracking (DIFT) has been proven an effective technique to track data usage; prevent control data attacks and non-control data attacks at runtime; and analyze program performance. Therefore, a series of DIFT techniques have been developed recently. In this paper, we summarize the current DIFT solutions and analyze the features and limitations of these solutions. Based on the analysis, we classify the existing solutions into three categories, i.e., software, hardware, software and hardware co-design. We discuss the DIFT design from the perspective of whole system and point out the limitations of current DIFT frameworks. Potential enhancements to these solutions are also presented. Furthermore, we present suggestions about the possible future direction of DIFT solutions so that DIFT can help improve security levels.
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Date   2021-07-29
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