Add to ORKGThis paper distinguishes malware families from a specific category (i.e., ransomware) via dynamic analysis. We collect samples from four ransomware families and use Cuckoo sandbox environment, to observe their runtime behaviour. This study aims to provide new insight into malware family classification by comparing possible runtime features, and application of different extraction and selection techniques on them. As we try many extraction models on call traces such as bag-of-words, ngram sequences and wildcard patterns, we also look for other behavioural features such as files, registry and mutex artefacts. While wildcard patterns on call traces are designed to overcome advanced evasion strategies such as the insertion of junk API calls (ca...
Recent progress in machine learning has led to promising results in behavioral malware detection. Be...
This paper proposes a scalable approach for distinguishing malicious files from clean files by inves...
Anti-malware vendors receive daily thousands of potentially malicious binaries to analyse and catego...
This paper distinguishes malware families from a specific category (i.e., ransomware) via dynamic an...
There exist different methods of identifying malware, and widespread method is the one found in almo...
Modern malware is designed with mutation characteristics, namely polymorphism and metamorphism, whic...
Modern malware is designed with mutation characteristics, namely polymorphism and metamorphism, whic...
Identifying families of malware is today considered a fundamental problem in the context of computer...
The staggering increase of malware families and their di- versity poses a significant threat and cre...
The skyrocketing growth rate of new malware brings novel challenges to protect computers and network...
Forensic analysis of executables or binary files is the common practice of detecting malware charact...
Despite the continued advancements in security research, malware persists as being a major threat in...
Anti-malware vendors receive daily thousands of potentially malicious binaries to analyse and catego...
Ransomware (RW) is a distinctive variety of malware that encrypts the files or locks the user’s syst...
Ransomware is a strain of malware that disables access to the user’s resources after infiltrating a ...
Recent progress in machine learning has led to promising results in behavioral malware detection. Be...
This paper proposes a scalable approach for distinguishing malicious files from clean files by inves...
Anti-malware vendors receive daily thousands of potentially malicious binaries to analyse and catego...
This paper distinguishes malware families from a specific category (i.e., ransomware) via dynamic an...
There exist different methods of identifying malware, and widespread method is the one found in almo...
Modern malware is designed with mutation characteristics, namely polymorphism and metamorphism, whic...
Modern malware is designed with mutation characteristics, namely polymorphism and metamorphism, whic...
Identifying families of malware is today considered a fundamental problem in the context of computer...
The staggering increase of malware families and their di- versity poses a significant threat and cre...
The skyrocketing growth rate of new malware brings novel challenges to protect computers and network...
Forensic analysis of executables or binary files is the common practice of detecting malware charact...
Despite the continued advancements in security research, malware persists as being a major threat in...
Anti-malware vendors receive daily thousands of potentially malicious binaries to analyse and catego...
Ransomware (RW) is a distinctive variety of malware that encrypts the files or locks the user’s syst...
Ransomware is a strain of malware that disables access to the user’s resources after infiltrating a ...
Recent progress in machine learning has led to promising results in behavioral malware detection. Be...
This paper proposes a scalable approach for distinguishing malicious files from clean files by inves...
Anti-malware vendors receive daily thousands of potentially malicious binaries to analyse and catego...