{'fraction_non_alphanumeric': 0.020134228187919462, 'fraction_numerical': 0.0, 'mean_word_length': 5.190311418685121, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Efficient Privacy-Preserving Access Control of Mobile Multimedia Data in Cloud Computing

With the nature of allowing the encryptor to define the access policy before encrypting a message, Ciphertext-policy attribute-based encryption (CP-ABE) has been widely adopted as a primitive to design cloud-assisted mobile multimedia data sharing system. However, in most previous works, the access policy sent along with ciphertext remains in the palintext form, which would expose the user’s privacy to anyone who can get the ciphertext even if he is not authorized to decrypt. In addition, the resource-constrained mobile devices can not carry out frequent encryption and decryption task caused by CP-ABE. Such drawbacks may reduce the enthusiasm of consumers to share the multimedia data via their mobile devices. In this paper, we proposed PPCMM, a privacy-preserving cloud-assisted mobile multimedia data sharing scheme, where each attribute is described by an attribute name and an attribute value. The attribute values are embedded in the chphertext and only the attribute names are revealed in the access policy. The encryption is divided to two phase: online and offline. In the offline stage, the data owner can prepare the intermediate ciphertext components. Once receiving the encryption requirement of a specific access policy and the multimedia data, the data owner can quickly form the final legal ciphertext in the online stage. By employing the decryption outsourcing technique, most computation overhead of matching test and decryption is offload to the cloud server. The security proof showed that PPCMM is adaptively secure in the standard model. The performance analysis indicated that PPCMM greatly reduces the computation cost in both online encryption and user decryption.