A Study on Similarity Calculation Method for API Invocation Sequences

Autor:	Eul Gyu Im, Tae Guen Kim, Yu Jin Shim
Rok vydání:	2015
Předmět:	Software_OPERATINGSYSTEMS Similarity (geometry) Theoretical computer science business.industry Computer science Static analysis computer.software_genre ComputingMilieux_MANAGEMENTOFCOMPUTINGANDINFORMATIONSYSTEMS Software Obfuscation Malware The Internet Data mining business computer
Zdroj:	Rough Sets and Knowledge Technology ISBN: 9783319257532 RSKT
DOI:	10.1007/978-3-319-25754-9_43
Popis:	Malware variants have been developed and spread in the Internet, and the number of new malware variants is increases every year. Recently, malware is applied with obfuscation and mutation techniques to hide its existence, and malware variants are developed with various automatic tools that transform the properties of existing malware to avoid static analysis based malware detection systems. It is difficult to detect such obfuscated malware with static-based signatures, so we have designed a detection system based on dynamic analysis. In this paper, we propose a dynamic analysis based system that uses the API invocation sequences to compare behaviors of suspicious software with behaviors of existing malware.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::835a022984c63536122a82188ade7ae6 https://doi.org/10.1007/978-3-319-25754-9_43 Zobrazit plný text záznamu