A conceptual scheme for ransomware background knowledge construction

Abstract

Various methods have been implemented to detect and mitigate malware. Ransomware is one of the rising malware which getting attention from world due to its impact of attack in the cyber space. Detection of potential features of Malware using traditional approach and usage of text mining is nothing new. However, identifying the Ransomware related entity from external sources and unstructured textual data like forum is new exposure towards the application of text mining in malware domain. Therefore, in this paper, a conceptual scheme is proposed to construct a Background Knowledge of Ransomware which necessary to improve the accuracy of NER when classifying the Ransomware related entity from unstructured data like online forum. From this work, the analysis related to malware also could be understood by people who have no or less expertise in Malware domain since it uses the casual text representation that are obtain from user-generated content made publicly.