[Paper Review] Attribute-based Multi-Signature and Encryption for EHR Management: A Blockchain-based Solution

Hao Guo, Wanxin Li+3 more|arXiv (Cornell University)|Feb 25, 2020

Cryptography and Data Security14 references4 citations

TL;DR

This paper proposes a blockchain-edge hybrid architecture for secure, privacy-preserving electronic health record (EHR) management using attribute-based multi-signature (ABMS) for anonymous patient authentication and multi-authority attribute-based encryption (ABE) for fine-grained access control. The system logs authentication and access events on Hyperledger Fabric blockchain while storing encrypted EHRs on edge nodes, achieving 32 ms signing and 243 ms verification times per attribute with linear scalability to 9 attributes.

ABSTRACT

The global Electronic Health Record (EHR) market is growing dramatically and has already hit $31.5 billion in 2018. To safeguard the security of EHR data and privacy of patients, fine-grained information access and sharing mechanisms are essential for EHR management. This paper proposes a hybrid architecture of blockchain and edge nodes to facilitate EHR management. In this architecture, we utilize attribute-based multi-signature (ABMS) scheme to authenticate user's signatures without revealing the sensitive information and multi-authority attribute-based encryption (ABE) scheme to encrypt EHR data which is stored on the edge node. We develop the blockchain module on Hyperledger Fabric platform and the ABMS module on Hyperledger Ursa library. We measure the signing and verifying time of the ABMS scheme under different settings, and experiment with the authentication events and access activities which are logged as transactions in blockchain.

Motivation & Objective

• To address the challenge of securing EHR data while enabling fine-grained, privacy-preserving access among healthcare providers.
• To prevent exposure of patient identities and sensitive information in public blockchains by using attribute-based signatures instead of identity-based ones.
• To overcome blockchain storage limitations by offloading large EHR data (e.g., medical images) to edge nodes.
• To ensure accountability and traceability of EHR access events through immutable blockchain logging.
• To evaluate the performance of ABMS signing and verification under varying attribute lengths and numbers.

Proposed method

• The system uses a hybrid architecture combining blockchain (Hyperledger Fabric) for logging authentication and access events, and edge nodes for storing ABE-encrypted EHR data.
• Attribute-based Multi-Signature (ABMS) is implemented via the BLS signature scheme on Hyperledger Ursa to enable anonymous, attribute-based authentication of patients.
• Multi-authority attribute-based encryption (CP-ABE) is used to encrypt EHR data on edge nodes, allowing access only to users with qualifying attributes.
• Smart contracts on Hyperledger Fabric enforce access policies, returning one-time self-destructing URLs to EHR data upon successful ABMS verification.
• The system uses one-time URLs (via 1ty.me) to securely share EHR access links that expire after a single use.
• Performance evaluation measures signing and verification times for ABMS under varying attribute lengths and numbers, with results logged on the blockchain.

Experimental results

Research questions

• RQ1 How can patient identity be authenticated without exposing sensitive personal information in EHR systems?
• RQ2 What is the performance overhead of attribute-based multi-signature schemes when scaling across multiple attributes?
• RQ3 Can a hybrid blockchain-edge architecture effectively balance data privacy, access control, and system scalability in EHR management?
• RQ4 How does the system ensure that only authorized healthcare providers can access EHRs based on their attributes?
• RQ5 What is the end-to-end latency of the authentication and EHR access workflow in a real-world deployment scenario?

Key findings

• ABMS signing time remains constant at approximately 32 ms regardless of attribute length, demonstrating independence from data size.
• ABMS verification time averages 243 ms per attribute and increases linearly with the number of attributes, due to the need for multiple bilinear pairings.
• The total verification time grows linearly with the number of attributes, with a 9-attribute signature taking roughly 9× the time of a single-attribute signature.
• The system successfully logs patient authentication and EHR access events as immutable transactions on the Hyperledger Fabric blockchain.
• The use of one-time self-destructing URLs ensures that EHR access links are valid only once, enhancing data confidentiality.
• The integration of ABMS and ABE with blockchain and edge storage enables secure, traceable, and fine-grained EHR access while preserving patient privacy.