期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：12
出版社：S&S Publications
摘要：Digital data unruffled for forensics analysis often contain expensive information about the suspects’social networks. However, most collected records are in the form of amorphous textual data, such as e-mails, chatmessages, and text documents. An investigator often has to manually extract the useful information from the text andthen enter the important pieces into a structured database for further investigation by using various criminal networkanalysis tools. Obviously, this information extraction process is monotonous and error-prone. Moreover, the quality ofthe analysis varies by the experience and expertise of the investigator. In this paper, we propose a systematic method todiscover criminal networks from a collection of text documents obtained from a suspect’s machine, extract usefulinformation for investigation, and then visualize the suspect’s criminal network. Furthermore, we present a hypothesisgeneration approach to identify potential indirect relationships among the members in the identified networks. Weevaluate the usefulness and recital of the method on a real-life cybercriminal case and some other datasets.
