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

By: Contributor(s): Series: SpringerBriefs in Computer SciencePublisher: New York, NY : Springer New York : Imprint: Springer, 2013Description: IX, 73 p. 15 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781461455233
Subject(s): Genre/Form: Additional physical formats: Printed edition:: No titleDDC classification:
  • 005.8 23
LOC classification:
  • QA76.9.A25
Online resources:
Contents:
Introduction -- Dynamic Binary Analysis Platform -- Hidden Code Extraction -- Privacy-breaching Behavior Analysis -- Hooking Behavior Analysis -- Analysis of Trigger Conditions and Hidden Behaviors -- Concluding Remarks.
In: Springer eBooksSummary: 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.
Item type: eBooks
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Introduction -- Dynamic Binary Analysis Platform -- Hidden Code Extraction -- Privacy-breaching Behavior Analysis -- Hooking Behavior Analysis -- Analysis of Trigger Conditions and Hidden Behaviors -- Concluding Remarks.

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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