Walid J. Ghandour, Clémentine Maurice (CNRS, CRIStAL)

Dynamic dependence analysis monitors information flow between instructions in a program at runtime. Strength-based dynamic dependence analysis quantifies the strength of each dependence chain by a measure computed based on the values induced at the source and target of the chain. To the best of our knowledge, there is currently no tool available that implements strength-based dynamic information flow analysis for x86.

This paper presents DITTANY, tool support for strength-based dynamic dependence analysis and experimental evidence of its effectiveness on the x86 platform. It involves two main components: 1) a Pin-based profiler that identifies dynamic dependences in a binary executable and records the associated values induced at their sources and targets, and 2) an analysis tool that computes the strengths of the identified dependences using information theoretic and statistical metrics applied on their associated values. We also study the relation between dynamic dependences and measurable information flow, and the usage of zero strength flows to enhance performance.

DITTANY is a building block that can be used in different contexts. We show its usage in data value and indirect branch predictions. Future work will use it in countermeasures against transient execution attacks and in the context of approximate computing.

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Weikeng Chen (DZK/UC Berkeley), Thang Hoang (Virginia Tech), Jorge Guajardo (Robert Bosch Research and Technology Center), Attila A. Yavuz (University of South Florida)

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Shengwei An (Purdue University), Guanhong Tao (Purdue University), Qiuling Xu (Purdue University), Yingqi Liu (Purdue University), Guangyu Shen (Purdue University), Yuan Yao (Nanjing University), Jingwei Xu (Nanjing University), Xiangyu Zhang (Purdue University)

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Ruotong Yu (Stevens Institute of Technology, University of Utah), Francesca Del Nin (University of Padua), Yuchen Zhang (Stevens Institute of Technology), Shan Huang (Stevens Institute of Technology), Pallavi Kaliyar (Norwegian University of Science and Technology), Sarah Zakto (Cyber Independent Testing Lab), Mauro Conti (University of Padua, Delft University of Technology), Georgios Portokalidis (Stevens Institute of…

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