Automatic Malware Analysis : An Emulator Based Approach / by Heng Yin, Dawn Song.

Por:

Yin, Heng [autor]

Colaborador(es):

Tipo de material: Texto

TextoSeries SpringerBriefs in Computer ScienceEditor: New York, NY : Springer New York : Imprint: Springer, 2013Descripción: Ix, 73 páginas 15 ilustraciones recurso en líneaTipo de contenido:

texto

Tipo de medio:

computadora

Tipo de portador:

recurso en línea

ISBN:

9781461455233

Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:

QA76.9.A25

Recursos en línea:

Conectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)

Contenidos:

Introduction -- Dynamic Binary Analysis Platform -- Hidden Code Extraction -- Privacy-breaching Behavior Analysis -- Hooking Behavior Analysis -- Analysis of Trigger Conditions and Hidden Behaviors -- Concluding Remarks.

Resumen: Malicious software (i.e., malware) has become a severe threat to interconnected computer systems for decades and has caused billions of dollars damages each year. A large volume of new malware samples are discovered daily. Even worse, malware is rapidly evolving becoming more sophisticated and evasive to strike against current malware analysis and defense systems. Automatic Malware Analysis presents a virtualized malware analysis framework that addresses common challenges in malware analysis. In regards to this new analysis framework, a series of analysis techniques for automatic malware analysis is developed. These techniques capture intrinsic characteristics of malware, and are well suited for dealing with new malware samples and attack mechanisms.

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Springer eBooks

Malicious software (i.e., malware) has become a severe threat to interconnected computer systems for decades and has caused billions of dollars damages each year. A large volume of new malware samples are discovered daily. Even worse, malware is rapidly evolving becoming more sophisticated and evasive to strike against current malware analysis and defense systems. Automatic Malware Analysis presents a virtualized malware analysis framework that addresses common challenges in malware analysis. In regards to this new analysis framework, a series of analysis techniques for automatic malware analysis is developed. These techniques capture intrinsic characteristics of malware, and are well suited for dealing with new malware samples and attack mechanisms.

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