Anomaly Detection Through Outsourced Revocable Identity-Based Signcryption With Equality Test for Sensitive Data in Consumer IoT Environments

Abstract

In the realm of consumer Internet of Things environments, data related to personal health and medical records can be collected. However, as this healthcare data falls under personal privacy, it must undergo encryption procedures before being uploaded to the cloud to ensure data confidentiality. Additionally, there is a desire for the encrypted data uploaded to the cloud to be compared, enabling the timely detection of anomalous data. If there are issues with healthcare data, the cloud system can issue alerts. Indeed, there already exists a mechanism, namely identity-based signcryption with equality test (IBSCET), which can accomplish the desire by comparing whether two encrypted data contain the same message. However, IBSCET does not address the issue of user revocation, which is crucial in any system. To address this problem, we enhance the existing IBSCET to propose the first outsourced revocable IBSCET (OR-IBSCET) scheme. Under the bilinear Diffie-Hellman and the computational Diffie-Hellman assumptions, we also demonstrate that the proposed scheme possesses security of the indistinguishability under chosen ciphertext attacks, the existential unforgeability under chosen message attacks, and one-wayness under chosen ciphertext attacks.