  Data privacy is one of the key challenges faced by enterprises today.
Anonymization techniques address this problem by sanitizing sensitive data such
that individual privacy is preserved while allowing enterprises to maintain and
share sensitive data. However, existing work on this problem make inherent
assumptions about the data that are impractical in day-to-day enterprise data
management scenarios. Further, application of existing anonymization schemes on
enterprise data could lead to adversarial attacks in which an intruder could
use information fusion techniques to inflict a privacy breach. In this paper,
we shed light on the shortcomings of current anonymization schemes in the
context of enterprise data. We define and experimentally demonstrate Web-based
Information- Fusion Attack on anonymized enterprise data. We formulate the
problem of Fusion Resilient Enterprise Data Anonymization and propose a
prototype solution to address this problem.
