Web browsing traces store a wealth of information that can be used to determine user activities and intentions. This study aims to analyze browsing traces such as site access history, cache data, and cookie files to identify behavioral patterns indicative of cybercrime. The methods used include data extraction, data cleaning, and pattern analysis with a simple statistical approach. The results of the study produce a list of patterns that serve as indicators of suspicious activity, as well as ways to present the analysis results in a form that is easy to understand and accountable.
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