Due to the rapid development of new technologies such as cloud computing, Internet of Things (IoT), and mobile Internet, the data volumes are exploding. Particularly, in the industrial field, a large amount of data is generated every day. How to manage and use industrial Big Data primely is a thorny challenge for every industrial enterprise manager. As an emerging form of service, cloud computing technology provides a good solution. It receives more and more attention and support due to its flexible configuration, on-demand purchase, and easy maintenance. Using cloud technology, enterprises get rid of the heavy data management work and concentrate on their main business. Although cloud technology has many advantages, there are still many problems in terms of security and privacy. To protect the confidentiality of the data, the mainstream solution is encrypting data before uploading. In order to achieve flexible access control to encrypted data, attribute-based encryption (ABE) is an outstanding candidate. At present, more and more applications are using ABE to ensure data security. However, the privacy protection issues during the key generation phase are not considered in the current ABE systems. That is to say, the key generation center (KGC) knows both of attributes and corresponding keys of each user. This problem is especially serious in the industrial big data scenario, because it will cause great damage to the business secrets of industrial enterprises. In this paper, we design a new ABE scheme that protects user’s privacy during key issuing. In our new scheme, we separate the functionality of attribute auditing and key generating to ensure that the KGC cannot know user’s attributes and that the attribute auditing center (AAC) cannot obtain the user’s secret key. This is ideal for many privacy-sensitive scenarios, such as industrial big data scenario.
Due to the rapid development of new technologies such as cloud computing, Internet of Things (IoT), and mobile Internet, the data volumes are exploding, and we have truly entered the era of “Big Data.” Big Data technology has been focused and applied to almost every industry, retail, healthcare, financial services, government, and so on. Particularly, in the field of industrial production, a large amount of data is generated every day, and it includes business data from information systems, machine data from industrial IoT systems, and some other data from related websites, etc. For a manufacturing enterprise, Big Data can not only be used to improve the efficiency of the business, but more importantly change the manufacturing process and business model. Industrial Big Data is the core of intelligent manufacturing and industrial IoT and provides the most favorable support for the development of Industry 4.0. How to manage and use industrial Big Data efficiently is a great challenge for every enterprise manager.
Cloud computing technology can provide better solutions to the above challenge. Using cloud technology, enterprises get rid of the heavy data management work and concentrate on their main business. Nowadays, large cloud service providers, such as Amazon, Microsoft, IBM, etc., have launched industrial cloud platforms, and more and more industrial enterprises migrate their data to these platforms. However, hosting data to third-party platforms will create new problems, because the security and privacy of the data have to depend on the credibility of the third-party. For businesses, the biggest concern is the confidentiality of industrial data. The main solution to this problem is to use encrypting methods to protect data before uploading it. However, traditional symmetric and asymmetric encryption schemes are not appropriate for providing fine-grained access control. Therefore, the above problems have brought new challenges to data encryption, and numerous studies have focused on these issues [
Among various solutions, attribute-based encryption (ABE) [
In order to solve the privacy protection problem in key generation phase, we propose a new ABE system, in which we separate the functionality of attribute auditing and key extracting to ensure that the KGC does not know the specific attributes of the user and that the attribute auditing center (AAC) does not obtain the user’s key. In this system, when user applies its private key, it authenticates its attributes to AAC first and gets a blind token, which only certificates its attributes blindly and reveals nothing about specific attributes. The user presents the blind token to the KGC to obtain the corresponding blind key, from which user can extract the final private key. During this process, no information about the user’s attributes is leaked to the KGC, and no information about the private key is leaked to the AAC. We implicitly use the oblivious transfer (OT) protocol to solve this problem. This protects the user’s privacy during key generation phase.
Our ABE is suitable for privacy sensitive scenarios. Particularly, in the encryption system of industrial cloud, the attributes often involve business secrets of industrial enterprises. KGC, as a technology department, should not know these types of secret information. Therefore, we expressly introduce an application of our new scheme in the industrial cloud.
Attribute-based encryption is a one-to-many public key encryption. Only the user, whose attributes satisfy the access policy set by the encryptor, can decrypt the ciphertext. This concept originates from identity-based encryption [
The concept of oblivious transfer (OT) is originally proposed by Rabin [
In 1985, Even et al. [
In Section
In CP-ABE system, there are three types of entities, i.e., key generation center (KGC), encryptor, and decryptor. The KGC issues secret key according to users’ attributes. The encryptor encrypts the messages according to a designated access policy. The decryptor can decrypt the ciphertext successfully only if its attributes satisfy the corresponding access policy.
There are four algorithms in a CP-ABE scheme:
The oblivious transfer (OT) protocol is a two-party computation protocol in which one party is the sender (
In this paper, we draw on a classic
Party
(a) If
(b) If
In addition,
Then,
Finally,
Let
In this paper, we use asymmetric bilinear groups; that is,
Let
The decision
In the key generation phase of traditional ABE, KGC always knows the attribute information of each user. This has greatly damaged the privacy of users. In order to solve this problem, we separate the two functions of attribute auditing and key extracting. We introduce an attribute audit center (AAC) in ABE system to authenticate the attributes of users and to make blind token for them. KGC, as a simple technical support institution, is only responsible for generating keys, but it does not know the corresponding attributes of these keys.
In the key generation phase (as shown in Figure
System model.
The specific process is as follows:
In detail, an attribute-based encryption with privacy preserving key generation scheme (PPKG-ABE) includes seven fundamental algorithms:
We note, in PPKG-ABE scheme, that AAC is responsible for auditing user’s attributes and issuing blind token
We define the security in two aspects: confidentiality and privacy. Specifically, in this security model, we do not allow AAC and KGC to collude.
We introduce the selective security model of choosing plaintext attacks for the PPKG-ABE scheme. The specific process is working between adversary
Repeats as Phase
The PPKG-ABE scheme is selectively IND-CPA secure if
We introduce a new security game for defining privacy. In this game, we define the following two oracles.
The specific process is working between adversary
Repeats as Phase
The PPKG-ABE scheme is privacy-protected in key generation phase, if
In this construction, the PPKG-ABE scheme is constructed on the basis of [
If the attribute
Then, it runs standard signature algorithm on
Then, it randomly chooses
The blind secret key
For
It outputs
We note, in the above key issuing procedure, that KGC cannot obtain the specific attributes of user, and AAC cannot obtain the secret key.
if
if
Then, it computes
The ciphertext is defined as
The correctness is guaranteed by
If the decisional
If the adversary
For
For
For
For
For
(a)
(b)
If
Therefore,
If the DDH assumption holds in
If DDH assumption holds in
Nowadays, new technological revolution represented by Big Data, cloud computing, and Internet of Things is changing the traditional industrial manufacturing system [ Industry Enterprise: in this system, the role of industry enterprise is data user. They want to get useful information according to their business, but they do not want to reveal their attributes information that may relate to their business secret to KGC. Industry Alliance Manager: in this system, the role of the industry alliance manager is AAC, which issues blind token for the attributes of industry enterprises after reviewing the relevant evidence. KGC: its responsibility is to issue the corresponding key to the attributes of industry enterprises. In this system, KGC cannot get these attributes. Industrial Information Provider: in this system, industrial information providers are the members of the industrial alliance and include manufacturing enterprises, sales enterprises, logistics enterprises, scientific research institutions, consultant firms, and so on. They will use ABE scheme to share their encrypted data. Industrial Cloud: industrial cloud serves as data storage center and data sharing center in this system. In order to protect security and privacy of industrial Big Data, the industrial information providers upload their data in encrypted form.
Application in industrial cloud.
The specific workflow is as follows: After checking the relevant evidence, the industry enterprise and the industry alliance manager run When the industry enterprises need to ask for their attributes keys, they will submit their blind tokens to KGC. The KGC runs After receiving the blind secret keys, the industry enterprises run The industrial information providers run The industry enterprises acquire encrypted data from the cloud and run
In the above application, industrial information providers can share industrial data according to enterprises’ attributes. Only the enterprises that meet the access policy are able to access data. Unlike traditional ABE solutions, in this application, the attributes information of enterprises will not be known by KGC. The business secret of enterprises is protected.
The data used to support the findings of this study are available from the corresponding author upon request.
The authors declare that they have no conflicts of interest.
This work is supported by the National Natural Science Foundation of China (No. 61602287, No. 61802235, No. 61672330, and No. 61702168), the Primary Research & Development Plan of Shandong Province (No. 2018GGX101037), and the Major Scientific and Technological Innovation Project of Shandong Province (No. 2018CXGC0702).