Abstract Symbolic Automata

Author:

Dalla Preda Mila1,Giacobazzi Roberto1,Lakhotia Arun2,Mastroeni Isabella1

Affiliation:

1. University of Verona, Verona, Italy

2. University of Louisiana, Lafayette, LA, USA

Abstract

We introduce a model for mixed syntactic/semantic approximation of programs based on symbolic finite automata (SFA). The edges of SFA are labeled by predicates whose semantics specifies the denotations that are allowed by the edge. We introduce the notion of abstract symbolic finite automaton (ASFA) where approximation is made by abstract interpretation of symbolic finite automata, acting both at syntactic (predicate) and semantic (denotation) level. We investigate in the details how the syntactic and semantic abstractions of SFA relate to each other and contribute to the determination of the recognized language. Then we introduce a family of transformations for simplifying ASFA. We apply this model to prove properties of commonly used tools for similarity analysis of binary executables. Following the structure of their control flow graphs, disassembled binary executables are represented as (concrete) SFA, where states are program points and predicates represent the (possibly infinite) I/O semantics of each basic block in a constraint form. Known tools for binary code analysis are viewed as specific choices of symbolic and semantic abstractions in our framework, making symbolic finite automata and their abstract interpretations a unifying model for comparing and reasoning about soundness and completeness of analyses of low-level code.

Funder

Air Force Research Laboratory

Ministero dell'Istruzione, dell'Università e della Ricerca

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Analyzing Dynamic Code;ACM Transactions on Privacy and Security;2021-05-31

2. The Power of Symbolic Automata and Transducers;Computer Aided Verification;2017

3. Obfuscation Code Localization Based on CFG Generation of Malware;Foundations and Practice of Security;2016

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