DCT sign based robust privacy preserving image copy detection for cloud-based systems

Abstract

In this paper we propose an architecture for message-privacy preserving copy detection and content identification for images based on the signs of the Discrete Cosine Transform (DCT) coefficients. The architecture allows for searching in encrypted data and places the computational burden on the server. Sign components of the low frequency DCT coefficients of an image are used to generate a dual set of keys that in turn are used to encrypt the source image and serve as a robust hash that can be queried for content identification. The statistical properties of these DCT sign vectors are modelled and we analyse their robustness against real world image distortions. Finally, the trade-off between the discriminative power of such vectors, the offered security and the resilience against errors is demonstrated.