The study of keyword search in open source search engines and digital forensics tools with respect to the needs of cyber crime investigations

This master thesis consists of both a theoretical and practical part. In the theoretical part of the thesis are three main parts of study: 1) Exploration of experimental search methodologies used in a Digital forensics setting. 2) Analysis of the differences in documented search capabilities between a set of open source search engines and open source forensics tools capable of keyword search. 3) Identified and summarized publicly available Digital forensic related datasets. For the first area of exploration no surveys published in the period 2014-2017 could be found. Therefore, this exploration tackles a missing gap in the current knowledge. The second exploration creates an in-depth and up-to-date analysis of differences in search capabilities, not found anywhere else. This analysis is useful for forensic examiners and researcher that want to know which application is most suitable for their problem domain. The third exploration extends previous lists of its kind, and adds many new unlisted forensic related datasets. This list, is to the best of my knowledge, the largest collection, of publicly forensic related datasets published in any paper. This addition in the paper will be useful for researchers in many subfields of Information security who are looking for a dataset to use in their research. Using publicly available datasets will also make their experiments more reproducible. Some of the datasets are also used in the practical part of the thesis. The practical part is a benchmark experiment where the open source search engines are tested on how well they perform at indexing, searching and memory performance during searching. Elasticsearch was generally better then Solr at index creation time, minimizing index size and response time for the first run of search terms. Solr outperformed Elasticsearch on second run of search terms. The difference between the search engines with regard to memory performance during searching was negligible. There are two main limitations with the experiment. The first being that the experiments are performed on only one virtual host machine. This environment does not allow testing for how well the search engines perform at distributed search. The second main issue is that only the default configurations was tested (out-of-the-box setup) with Solr and Elasticsearch. If more configurations had been tested, then some of the variables such as sharding and segment count could be controlled. Up-to-date experiments with the same testing methodology could not be found. The experiments provide information that is useful for forensic examiners when deciding which search engine is best suitable for their forensics tasks