Investigating network and computer related crime requires the combination of heterogeneous sources of reliable evidential weight. Information such as name, surname, email address, login details, social network account and banking details may provide insight on the identity of the device, however, it does not guarantee the identity of the entity using the device. Several sources of potential evidence have been adapted for digital investigation processes. As a probable complementary source of evidence, this study proposed the integration of the semantic properties of web-browser history into digital forensics. To achieve this aim, the study developed a web-browser analysis tool which is independent of the type of browser. Experimental process was carried using nine users. Cosine and Jaccard similarity functions and motifs similarity measures were used to explore the probability of attributing a user based on web-browser history data. The result substantiates the theoretical assertion of the reliability of the semantic characteristics of web-browser information. Using the developed tool and the semantic properties of web-browser data, a forensic investigator can complement the evidential weight of potential digital evidence used in a forensic investigation. This result can also be used as a complementary metrics for strengthening security and digital forensic auditing process.
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