Preprocessing of Binary Executable Files Towards Retargetable Decompilation
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F13%3APU106299" target="_blank" >RIV/00216305:26230/13:PU106299 - isvavai.cz</a>
Výsledek na webu
<a href="http://www.thinkmind.org/index.php?view=article&articleid=iccgi_2013_13_10_10061" target="_blank" >http://www.thinkmind.org/index.php?view=article&articleid=iccgi_2013_13_10_10061</a>
DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Preprocessing of Binary Executable Files Towards Retargetable Decompilation
Popis výsledku v původním jazyce
The goal of retargetable machine-code decompilation is to analyze and reversely translate platform-dependent executable files into a high level language (HLL) representation. This process can be used for many different purposes, such as legacy code reengineering, malware analysis, etc. Retargetable decompilation is a complex task that must deal with a lot of different platform-specific features and missing information. Moreover, input files are often compressed or protected from any kind of analysis (up to 80% of malware samples). Therefore, accurate preprocessing of input files is one of the necessary prerequisites in order to achieve the best results. This paper presents a concept of a generic preprocessing system that consists of a precise signature-based compiler and packer detector, plugin-based unpacker, and converter into an internal platform-independent file format. This approach has been adopted and tested in an existing retargetable decompiler. According to our experimental results, the proposed retargetable solution is fully competitive with existing platform-dependent tools.
Název v anglickém jazyce
Preprocessing of Binary Executable Files Towards Retargetable Decompilation
Popis výsledku anglicky
The goal of retargetable machine-code decompilation is to analyze and reversely translate platform-dependent executable files into a high level language (HLL) representation. This process can be used for many different purposes, such as legacy code reengineering, malware analysis, etc. Retargetable decompilation is a complex task that must deal with a lot of different platform-specific features and missing information. Moreover, input files are often compressed or protected from any kind of analysis (up to 80% of malware samples). Therefore, accurate preprocessing of input files is one of the necessary prerequisites in order to achieve the best results. This paper presents a concept of a generic preprocessing system that consists of a precise signature-based compiler and packer detector, plugin-based unpacker, and converter into an internal platform-independent file format. This approach has been adopted and tested in an existing retargetable decompiler. According to our experimental results, the proposed retargetable solution is fully competitive with existing platform-dependent tools.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
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OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2013
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
8th International Multi-Conference on Computing in the Global Information Technology (ICCGI'13)
ISBN
978-1-61208-283-7
ISSN
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e-ISSN
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Počet stran výsledku
6
Strana od-do
259-264
Název nakladatele
International Academy, Research, and Industry Association
Místo vydání
Nice
Místo konání akce
Nice
Datum konání akce
21. 7. 2013
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
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