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arXiv Machine Learning By Mohammad Waquas Usmani, Susmit Shannigrahi, Michael Zink

Learning-Based Reconstruction Attacks on Coordinate-Obfuscated Point Clouds

Read the original on arXiv Machine Learning →

The paper investigates the security of a selective coordinate encryption scheme for point clouds used in volumetric video. By training PointNet and Random Forest models on partially encrypted data, the authors show that fully encrypting all X coordinates is difficult to reconstruct, whereas encrypting every second X coordinate allows accurate recovery of the hidden values. The study highlights that the encryption granularity critically determines the vulnerability of the scheme.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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