Due to the extensive use of various intelligent terminals and the popularity of network social tools, a large amount of data in the field of medical emerged. How to manage these massive data safely and reliably has become an important challenge for the medical network community. This paper proposes a data management framework of medical network community based on Consortium Blockchain (

With the accelerating process of digitization of medical systems in various countries, medical data shows an exponential upward trend [

In the medical network community, the patient’s personal information data and condition information will be recorded to form big data [

Security and privacy of data management are priorities [

We organize the rest of this article as follows. The second section introduces the related work, and the third section mainly constructs the data security management framework of medical network community based on

The ideal medical data management scheme should meet the following basic requirements, namely security and privacy protection [

Security and privacy protection: no one may illegally use medical data. The program should be able to ensure that the data resists illegal attacks.

Data access: after obtaining the authorization, the research institution can view all relevant medical records, and the research institution can access the previous medical information under the authorization of the medical institution.

Access control: only medical institutions can manage patient data, that is, no one can obtain historical data without the consent of the medical institution.

Unified standards: unified data management standards should be adopted in the model to balance the overall stability of the system.

The powerful, robust, flexible and secure functions of

Providing a trusted mechanism for all participants of

Some researchers use blockchain as a secure distributed ledger, which provides a potential solution for cross system management of medical information. Li et al. [

In the process of

In the medical network community, data security is the premise of medical big data management.

In order to make up for the lack of privacy protection of important data in

Consortium Blockchain network: as a part of the blockchain [

Federated learning network: providing a trusted mechanism for all participants of federated learning through

Entity: including research institutions and medical institutions. The mechanism of

In the medical network community, in order to consider the security of private data, public key encryption schemes are usually used to hide medical data. However, the fact that homomorphic public key encryption schemes are vulnerable to (adaptive) ciphertext selection attacks has been ignored to some extent. Theoretically, the adversary sends a homomorphic evaluation challenge ciphertext to the decryption oracle, and can immediately destroy the security. Therefore, we use the

Definition 1 (

So far, the above

Definition 2 (correctness). For all

Definition 3 (

It can be ignored in

Evaluate oracle

Homomorphic key disclosures oracle

Decryption prophecy

Lemma 1. Under the

Proof. Suppose that the effective adversary

Algorithm

Select

When

Sampling

If

Otherwise, returns 0.

If

If

Therefore, the probability of

In the medical network community environment, assuming that

In the above data sharing process, we can all know the medical data t shared from

This section constructs an efficient

That is,

Run

That is

Therefore, the integer signature value

After receiving the group signature, the verifier returns

Private key:

Public key:

Encrypted data:

According to the rules of sharing smart contract of medical data security, in the data sharing scenario, we explain how to construct a data sharing sentence

Assume that

The proof language

The data sharing sentence

Proof generation by

Certifier

Proof of formula (A-F) through

Finally,

The verifier

Theorem 1. Assuming

Proof. The following describes our proof conclusion.

Perfect Completeness. This property can be directly verified.

Soundness. It is assumed that the

Then, construct the extractor Ext:

Verifier information can be extracted by calculation (for

Under the condition of extracting the prover, if

Perfect zero knowledge. Construct a simulated

The parameters are divided into 3 parts:

For clarity and convenience, we express the simulation parameters as

Set

In the argument of simulation, under the same conditions, the given value

The Fiat-Shamir heuristic algorithm is applied to the

Set the set of

Under the condition of

Set

Combining

(perfect) get zero knowledge property. The next step is to verify the correctness of

In the formula above, only two pairing calculations are calculated, which is more efficient than (

If

1)

2) There are some

That is, the probability is negative because

Overall, the overwhelming probability is

In this section, the

Subsequently, the computational complexity of

Proof size | Hyrax [ |
Bulletproofs [ |
ZKSNARK [ |
This paper |
---|---|---|---|---|

Theoretical | ||||

Practical | 3.2 MB | 2115 B | 735 KB | 3260 B |

In order to verify the effectiveness of the overall scheme, this paper cites the medical dataset of the National Institutes of Health in the United States to evaluate the scheme. Firstly, we trained 60 epochs in the ensemble environment and used the

Secondly, in order to test the accuracy of the medical dataset in the

This paper presents a data management framework of medical network community based on