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Simultaneous Localization and Mapping is widespread in both robotics and autonomous driving. This paper proposes a novel method to identify changes in maps constructed by SLAM algorithms without feature-to-feature comparison. We use ICP-like algorithms to match frames and pose graph optimization to solve the SLAM problem. Finally, we analyze the residuals to localize possible alterations of the map. The concept was tested with 2D LIDAR SLAM problems in simulated and real-life cases.