Authors: Jay Koven (NYU Tandon School of Engineering), Enrico Bertini (NYU Tandon School of Engineering), Luke Dubois (NYU Tandon School of Engineering), Nasir Memon (NYU Tandon School of Engineering)
DFRWS USA 2016
Abstract
Large email data sets are often the focus of criminal and civil investigations. This has created a daunting task for investigators due to the extraordinary size of many of these collections. Our work offers an interactive visual analytic alternative to the current, manually intensive methodology used in the search for evidence in large email data sets. These sets usually contain many emails which are irrelevant to an investigation, forcing investigators to manually comb through information in order to find relevant emails, a process which is costly in terms of both time and money. To aid the investigative process we combine intelligent preprocessing, a context-aware visual search, and results display that presents an integrated view of diverse information contained within emails. This allows an investigator to reduce the number of emails that need to be viewed in detail without the current tedious manual search and comb process.