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BYTERI : = Byte Resonance Imaging of Binary Executables.
Record Type:
Language materials, manuscript : Monograph/item
Title/Author:
BYTERI :/
Reminder of title:
Byte Resonance Imaging of Binary Executables.
Author:
Narasimha, Seshagiri Prabhu.
Description:
1 online resource (218 pages)
Notes:
Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
Contained By:
Dissertations Abstracts International85-12B.
Subject:
Computer science. -
Online resource:
click for full text (PQDT)
ISBN:
9798383179239
BYTERI : = Byte Resonance Imaging of Binary Executables.
Narasimha, Seshagiri Prabhu.
BYTERI :
Byte Resonance Imaging of Binary Executables. - 1 online resource (218 pages)
Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
Thesis (Ph.D.)--University of Louisiana at Lafayette, 2024.
Includes bibliographical references
Knowledge of the input format of binary executables is important for finding bugs and vulnerabilities, such as generating data for fuzzing or manual reverse engineering. This dissertation presents two algorithms that leverage dynamic taint analysis to recover the structure of the input of binary executables.These algorithms improve upon prior work by not just partitioning the input into consecutive bytes representing values but also identifying syntactic components of structures, such as fixed and variable-length fields, nested structures, and simple arrays. Notably, the second algorithm additionally infers different array types, including arrays of atomic fields, arrays of records, arrays with variant records, and even semantic relationships between fields, such as a field specifying the total number of elements of an array.The first algorithm infers a recursive state machine (RSM) representing the syntactic structure, while the second one recovers the structure in a C/C++-like notation capturing both syntactic structure and semantic relations between fields of the input. An additional algorithm is introduced to combine structures from multiple inputs, making it feasible to create an abstract structure that represents a more complete space of input data acceptable to a binary executable.The algorithms were implemented in prototype systems named BYTERI-1.0 and BYTERI-2.0 (Byte Resonance Imaging). The evaluation involved a controlled experiment using synthetic programs mimicking real-world formats (PE, PNG, BMP, and CSV) and real-world programs (parsers for BMP, PNG, GIF, TIFF, ZIP, PDF, XML linter, and a disassembler). Both BYTERI-1.0 and BYTERI-2.0 correctly identified the syntactic structure. Additionally, BYTERI-2.0 successfully inferred semantic relations between fields.Furthermore, the recovered structures were used to generate valid input data. BYTERI-1.0 succeeded when the syntax was not context-sensitive, such as when a field specifies the length of a variable-length field. BYTERI-2.0-generated data was valid for all synthetic programs and some real-world ones.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024
Mode of access: World Wide Web
ISBN: 9798383179239Subjects--Topical Terms:
573171
Computer science.
Subjects--Index Terms:
Dynamic taint analysisIndex Terms--Genre/Form:
554714
Electronic books.
BYTERI : = Byte Resonance Imaging of Binary Executables.
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Byte Resonance Imaging of Binary Executables.
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Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
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Advisor: Lakhotia, Arun.
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Thesis (Ph.D.)--University of Louisiana at Lafayette, 2024.
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Includes bibliographical references
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Knowledge of the input format of binary executables is important for finding bugs and vulnerabilities, such as generating data for fuzzing or manual reverse engineering. This dissertation presents two algorithms that leverage dynamic taint analysis to recover the structure of the input of binary executables.These algorithms improve upon prior work by not just partitioning the input into consecutive bytes representing values but also identifying syntactic components of structures, such as fixed and variable-length fields, nested structures, and simple arrays. Notably, the second algorithm additionally infers different array types, including arrays of atomic fields, arrays of records, arrays with variant records, and even semantic relationships between fields, such as a field specifying the total number of elements of an array.The first algorithm infers a recursive state machine (RSM) representing the syntactic structure, while the second one recovers the structure in a C/C++-like notation capturing both syntactic structure and semantic relations between fields of the input. An additional algorithm is introduced to combine structures from multiple inputs, making it feasible to create an abstract structure that represents a more complete space of input data acceptable to a binary executable.The algorithms were implemented in prototype systems named BYTERI-1.0 and BYTERI-2.0 (Byte Resonance Imaging). The evaluation involved a controlled experiment using synthetic programs mimicking real-world formats (PE, PNG, BMP, and CSV) and real-world programs (parsers for BMP, PNG, GIF, TIFF, ZIP, PDF, XML linter, and a disassembler). Both BYTERI-1.0 and BYTERI-2.0 correctly identified the syntactic structure. Additionally, BYTERI-2.0 successfully inferred semantic relations between fields.Furthermore, the recovered structures were used to generate valid input data. BYTERI-1.0 succeeded when the syntax was not context-sensitive, such as when a field specifies the length of a variable-length field. BYTERI-2.0-generated data was valid for all synthetic programs and some real-world ones.
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Ann Arbor, Mich. :
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ProQuest,
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2024
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Mode of access: World Wide Web
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31244335
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click for full text (PQDT)
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