Visible to the public Dynamic Malware Detection Using API Similarity

TitleDynamic Malware Detection Using API Similarity
Publication TypeConference Paper
Year of Publication2017
AuthorsAlkhateeb, E. M. S.
Conference Name2017 IEEE International Conference on Computer and Information Technology (CIT)
Date Publishedaug
ISBN Number978-1-5386-0958-3
KeywordsAPI, API similarity, APIs, application program interfaces, compositionality, Computer crime, credit card, credit card details, data mining, dynamic Malware detection method, feature extraction, hacker, Information security, invasive software, Malware, malware analysis, malware samples, malware-detection method, Pattern matching, pubcrawl, resilience, Resiliency, Sea measurements, Tools, trojan, Trojan horses, Trojans, user-confidential information

Hackers create different types of Malware such as Trojans which they use to steal user-confidential information (e.g. credit card details) with a few simple commands, recent malware however has been created intelligently and in an uncontrolled size, which puts malware analysis as one of the top important subjects of information security. This paper proposes an efficient dynamic malware-detection method based on API similarity. This proposed method outperform the traditional signature-based detection method. The experiment evaluated 197 malware samples and the proposed method showed promising results of correctly identified malware.

Citation Keyalkhateeb_dynamic_2017