Biblio

With the increased popularity of ubiquitous computing and connectivity, the Internet of Things (IoT) also introduces new vulnerabilities and attack vectors. While secure data collection (i.e. the upward link) has been well studied in the literature, secure data dissemination (i.e. the downward link) remains an open problem. Attribute-based encryption (ABE) and outsourced-ABE has been used for secure message distribution in IoT, however, existing mechanisms suffer from extensive computation and/or privacy issues. In this paper, we explore the problem of privacy-preserving targeted broadcast in IoT. We propose two multi-cloud-based outsourced-ABE schemes, namely the parallel-cloud ABE and the chain-cloud ABE, which enable the receivers to partially outsource the computationally expensive decryption operations to the clouds, while preventing user attributes from being disclosed. In particular, the proposed solution protects three types of privacy (i.e., data, attribute and access policy privacy) by enforcing collaborations among multiple clouds. Our schemes also provide delegation verifiability that allows the receivers to verify whether the clouds have faithfully performed the outsourced operations. We extensively analyze the security guarantees of the proposed mechanisms and demonstrate the effectiveness and efficiency of our schemes with simulated resource-constrained IoT devices, which outsource operations to Amazon EC2 and Microsoft Azure.