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Modern network security research has demonstrated a clear necessity for open sharing of traffic datasets between organizations a need that has so far been superseded by the challenges of removing sensitive content from the data beforehand. Network Data Anonymization is an emerging field dedicated to solving this problem, with a main focus on removal of identifiable artifacts that might pierce privacy, such as usernames and IP addresses. However, recent research has demonstrated that more subtle statistical artifacts, also present, may yield fingerprints that are just as differentiable as the former.
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