Notoriously, immutability is one of the most striking properties of blockchains. As the data contained in blockchains may be compelled to redact for personal and legal reasons, immutability needs to be skillfully broken. In most existing redactable blockchains, fine-grained redaction and effective deletion of harmful data are mutually exclusive. To close the gap, we propose a fine-grained and controllably redactable blockchain with harmful data forced removal. In the scheme, the originator of the transaction has fine-grained control over who can perform the redaction and which portions of the transaction can be redacted. The redaction transaction is performed after collecting enough votes from miners. All users can provide the index of the block containing the harmful data to receive rewards, which are borne by the malicious user who initially posted the data. Miners can forcibly remove the harmful data based on the index. The malicious user will be blacklisted if the reward is not paid within a period of time, and any transaction about such user will not be performed later. In addition, the scheme supports the redaction of additional data and unexpended transaction output (UTXO) simultaneously. We demonstrate that the scheme is secure and feasible via formal security analysis and proof-of-concept implementation.

Cloud-based VANETs are designed to enable communication between high-speed vehicles. In such a highly dynamic environment, how to provide secure and anonymous communication service is a challenge. In this article, we affirmatively address the challenge by proposing a traitor-resistant and dynamic anonymous communication framework (TD-ACF) for cloud-based VANETs, which supports several advantageous features. In TD-ACF, each vehicle is represented by a set of attributes instead of its real identity, and the driving data is transmitted in encrypted form. Therefore, the anonymous authentication and the confidentiality of driving data are achieved in this way. Meanwhile, TD-ACF supports two practical requirements in cloud-based VANETs: the revocation and the traceability of traitor. For the former, TD-ACF can force a vehicle to exit the communication network at any moment. We employ an efficient binary tree algorithm to reduce the size of key updates for revocation from the traditional linear to the logarithmic level. For the latter, we overcome the barrier of the one-to-many relationship between a vehicle and the shared set of attributes to support traitor tracing. In TD-ACF, unlike most existing schemes, the Semi-Trusted Cloud (STC) can directly capture and punish a traitor instead of querying all the records in the list of unrevoked vehicles. In addition, we solve the key escrow problem that plagues most existing attribute-based schemes. The theoretical analysis and experimental simulation show that the proposed scheme is feasible and effective.

With the increasing cloud storage service, users can enjoy non-interactive data sharing. Nonetheless, the data owner cannot timely update the shared data all the while. To ensure the timeliness and the authoritative source of the data, some users should be allowed to update the data on behalf of an authoritative data owner without changing data source. However, this allows harmful information to be injected into the data unnoticeably. How to efficiently realize editable cloud-based data sharing supporting malicious user tracing has not been fully explored. To address the problem, we propose a fine-grained and controllably editable cloud-based data sharing scheme with malicious user accountability. The data owner only needs to sign the shared data before uploading it and can specify a fine-grained access control policy about who can update the data and which portions of the data can be updated. The authorized users non-interactively convert signatures of original data into new ones for the updated data, which are indistinguishable from the original signatures. The proposed scheme also supports malicious user accountability in the sense that malicious users who post harmful information can be traced. We demonstrate the security and practicality of our scheme via formal security analysis and extensive experiments.

IoT-connected healthcare sensor networks require authenticated and privacy-preserving data exchange among wearable sensors, mobile medical terminals, edge gateways, cloud servers, and medical institutions. Existing authentication schemes for healthcare IoT often bind signatures directly to user identities, exposing sensitive personal or institutional information and imposing heavy verification costs on resource-constrained sensing devices. To address this problem, we propose a fine-grained and flexible dual authentication scheme for healthcare sensor networks. In the proposed scheme, health data and diagnoses are signed with a fresh signing key and a fine-grained access control policy each time, so that the signer identity remains hidden while authorized entities can still modify permitted parts of signed data. No entity other than an authorized entity can trace a malicious signer or modify signed data without changing the data source. To support lightweight verification in sensor-edge-cloud deployments, we further present a verifiable outsourced authentication scheme that outsources time-consuming pairing operations to cloud servers; the online verification process then requires only six multiplication operations. As a fundamental technical component, we present a practical attribute-based sanitizable signature with shorter signature and key lengths and more efficient signing and signature-changing operations than the state-of-the-art policy-based sanitizable signature (P3S). Formal security analysis and experiments demonstrate the security and practicality of the proposed scheme for privacy-preserving healthcare sensing and medical data exchange.

IoT-connected healthcare sensor networks require authenticated and privacy-preserving data exchange among wearable sensors, mobile medical terminals, edge gateways, cloud servers, and medical institutions. Existing authentication schemes for healthcare IoT often bind signatures directly to user identities, exposing sensitive personal or institutional information and imposing heavy verification costs on resource-constrained sensing devices. To address this problem, we propose a fine-grained and flexible dual authentication scheme for healthcare sensor networks. In the proposed scheme, health data and diagnoses are signed with a fresh signing key and a fine-grained access control policy each time, so that the signer identity remains hidden while authorized entities can still modify permitted parts of signed data. No entity other than an authorized entity can trace a malicious signer or modify signed data without changing the data source. To support lightweight verification in sensor-edge-cloud deployments, we further present a verifiable outsourced authentication scheme that outsources time-consuming pairing operations to cloud servers; the online verification process then requires only six multiplication operations. As a fundamental technical component, we present a practical attribute-based sanitizable signature with shorter signature and key lengths and more efficient signing and signature-changing operations than the state-of-the-art policy-based sanitizable signature (P3S). Formal security analysis and experiments demonstrate the security and practicality of the proposed scheme for privacy-preserving healthcare sensing and medical data exchange.