Reinforcing privacy in cloud computing via adaptively secure non-zero inner product encryption and anonymous identity-based revocation in unbounded setting

Abstract

Cloud computing serves as an advanced computing technology to support Internet services and has numerous applications, including medical fields, online data storage, social network, big data analysis, and e-learning platforms. Inner product encryption (IPE) is a promising cryptographic primitive that facilitates access control over outsourced encrypted data by restricting decryption capability via an inner product relation. Most of the existing IPEs are built assuming a priori bound on the length of attribute vectors associated with the plane data. A situation may occur when adding new attributes is essential due to upgradation. Thus it is desirable to construct IPE with variable length attribute vectors instead of fixing the length at the setup phase. Such IPEs are more flexible while encrypting data and consequently have more real-life applications. In the following, we make our contributions:–We design the first efficient adaptively payload-hiding secure unbounded non-zero IPE (UNIPE) scheme from the standard symmetric external Diffie-Hellman (SXDH) assumption and prove security in the standard model.–We propose a generic construction of an adaptively weak attribute-hidingUNIPE from an unbounded inner product functional encryption (UIPFE) scheme. We also instantiate UNIPE from the SXDH assumption and prove security in the standard model.–Finally, we present the first unbounded anonymous identity-based revocation (UAnon-IBRV) scheme using our generic UNIPE as the building block. The anonymity feature ensures that the ciphertext reveals no information about the revoking sets of the system.