Contextual Identification of Windows Malware through Semantic Interpretation of API Call Sequence

Malware Characterization Using Windows API Call Sequences

Malware Detection using Windows API Sequence and Machine Learning

Monitoring the behavior of program execution at run-time is widely used to differentiate benign and malicious processes executing in the host computer. Most of the existing run-time malware detection methods use the information available in Windows Application Programming Interface (API) calls. The proposed malware detection system uses the Windows API call sequence. A 3rd order Markov chain (i...

the effect of vocabulary instruction through semantic mapping on learning and recall of efl learners

چکیده ندارد.

Malware Similarity Analysis using API Sequence Alignments

Malware variants could be defined as malware that have similar malcious behavior. In this paper, a sequence alignment method, the method widely used in Bioinformatics, was used to detect malware variants. This method can find the common parts of Malware’s API call sequences, and these common API call sequences can be used to detect similar behaviors of malware variants. However, when a sequence...

Android Malware Detection Using Library API Call Tracing and Semantic-Preserving Signal Processing Techniques

We propose to develop a new malware detection mechanism for Android-based mobile devices based upon library API call tracing and signal processing techniques. By tracing and utilizing library API calls we can capture the intentions/behaviors of an application at a higher level. Also, signal processing techniques, such as a wavelet-based transformation, may have the advantage of enhanced flexibi...