02696nam 2200589 a 450 991043757880332120200520144314.01-283-62478-897866139372301-4614-5523-510.1007/978-1-4614-5523-3(CKB)2670000000246531(EBL)1030912(OCoLC)811139541(SSID)ssj0000766940(PQKBManifestationID)11513375(PQKBTitleCode)TC0000766940(PQKBWorkID)10740508(PQKB)10085661(DE-He213)978-1-4614-5523-3(MiAaPQ)EBC1030912(PPN)168303264(EXLCZ)99267000000024653120120731d2013 uy 0engur|n|---|||||txtccrAutomatic malware analysis an emulator based approach /Heng Yin, Dawn Song1st ed. 2013.New York Springer20131 online resource (82 p.)SpringerBriefs in computer science,2191-5768Description based upon print version of record.1-4614-5522-7 Includes bibliographical references.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.SpringerBriefs in Computer Science,2191-5768Malware (Computer software)Malware (Computer software)005.8Yin Heng1058565Song Dawn1383096MiAaPQMiAaPQMiAaPQBOOK9910437578803321Automatic malware analysis4192904UNINA