Image Deduplication Based on Hashing and Clustering in Cloud Storage

• Lu Chen,
• Feng Xiang,
• Zhixin Sun,

Vol. 15, No. 4, April 30, 2021
10.3837/tiis.2021.04.014, Download Paper (Free):

• Cloud Storage
• clustering
• Image Deduplication
• Perceptual Hash
• feature extraction

Abstract

With the continuous development of cloud storage, plenty of redundant data exists in cloud storage, especially multimedia data such as images and videos. Data deduplication is a data reduction technology that significantly reduces storage requirements and increases bandwidth efficiency. To ensure data security, users typically encrypt data before uploading it. However, there is a contradiction between data encryption and deduplication. Existing deduplication methods for regular files cannot be applied to image deduplication because images need to be detected based on visual content. In this paper, we propose a secure image deduplication scheme based on hashing and clustering, which combines a novel perceptual hash algorithm based on Local Binary Pattern. In this scheme, the hash value of the image is used as the fingerprint to perform deduplication, and the image is transmitted in an encrypted form. Images are clustered to reduce the time complexity of deduplication. The proposed scheme can ensure the security of images and improve deduplication accuracy. The comparison with other image deduplication schemes demonstrates that our scheme has somewhat better performance.

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