From Debugging-Information Based Binary-Level Type Inference to CFG Generation

Author:

Zeng Dongrui1,Tan Gang1

Affiliation:

1. Pennsylvania State University, State College, PA, USA

Funder

US NSF

Defense Advanced Research Projects Agency (DARPA)

Office of Naval Research

Publisher

ACM

Cited by 16 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 and revivifying function signature inference using deep learning;Empirical Software Engineering;2024-05

2. Plankton: Reconciling Binary Code and Debug Information;Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2;2024-04-27

3. Scheduled Execution-Based Binary Indirect Call Targets Refinement;Lecture Notes in Computer Science;2024

4. TypeSqueezer: When Static Recovery of Function Signatures for Binary Executables Meets Dynamic Analysis;Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security;2023-11-15

5. μDep: Mutation-Based Dependency Generation for Precise Taint Analysis on Android Native Code;IEEE Transactions on Dependable and Secure Computing;2023-03-01

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