Deep Graph Learning for Circuit Deobfuscation.

Chen, Zhiqian; Zhang, Lei; Kolhe, Gaurav; Kamali, Hadi Mardani; Rafatirad, Setareh; Pudukotai Dinakarrao, Sai Manoj; Homayoun, Houman; Lu, Chang-Tien; Zhao, Liang

Chen, Zhiqian; Zhang, Lei; Kolhe, Gaurav; Kamali, Hadi Mardani; Rafatirad, Setareh; Pudukotai Dinakarrao, Sai Manoj; Homayoun, Houman; Lu, Chang-Tien; Zhao, Liang.

Afiliación

Chen Z; Department of Computer Science and Engineering, Mississippi State University, Starkville, MS, United States.
Zhang L; Department of Computer Science, Virginia Tech, Falls Church, VA, United States.
Kolhe G; Electrical and Computer Engineering Department, University of California, Davis, Davis, CA, United States.
Kamali HM; Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, United States.
Rafatirad S; Computer Science, University of California, Davis, Davis, CA, United States.
Pudukotai Dinakarrao SM; Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, United States.
Homayoun H; Department of Computer Science, Emory University, Atlanta, GA, United States.
Lu CT; Department of Computer Science, Virginia Tech, Falls Church, VA, United States.
Zhao L; Computer Science, University of California, Davis, Davis, CA, United States.

Front Big Data ; 4: 608286, 2021.

Article en En | MEDLINE | ID: mdl-34109310

Palabras clave

circuit deobfuscation; deep learning; graph mining; graph neural networks; satisfiability checking

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Big Data Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

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