Obfuscating EVES Algorithm and Its Application in Fair Electronic Transactions in Public Clouds

As the aging population of society continues to intensify, the series of problems brought about by aging is becoming more and more serious. Because the health problem of the elderly brings many social problems, people have paid close attention to it. Fortunately, as a typical smart healthcare system, wireless body area networks (WBANs) present quit nice medical care for people, especially the aged. However, personal health information is very sensitive. But, the common communication channel is used in WBANs and any malicious entity can initiate a security attack on WBANs. To ensure secure communication and privacy-preserving which are the premise of the sound development of WBANs, an improved and efficient certificateless authentication scheme with conditional privacy-preserving is proposed in this paper on the basis of analyzing the most recent presented certificateless authentication scheme for WBANs. The proposed scheme also provides batch authentication to decrease authentication and communication cost. A rigid security proof demonstrates that our proposed scheme resists every type of security attack and can provide condition privacy-preserving. The performance analysis shows that our proposed scheme has some advantages in computation and communication cost.

Section: Related Workmentioning

confidence: 99%

CasCP: Efficient and Secure Certificateless Authentication Scheme for Wireless Body Area Networks with Conditional Privacy-Preserving

Xie

Zhang

et al. 2019

“…There was a long-standing open feasibility problem in cryptography: Does there exist a functional encryption scheme supporting all polynomial-size circuits? Until 2013, Garg et al [23] had shown a method to construct functional encryption schemes for polynomial-size circuits based on the indistinguishability obfuscation [24]. Functional encryption has most powerful expressive ability, which can express identitybased encryption (IBE) [25,26], ABE [27,28], predicate encryption [14,15], and inner product encryption [15,29].…”

Section: Related Work Querying On Encrypted Data Is a Long-termmentioning

confidence: 99%

An Approach Enabling Various Queries on Encrypted Industrial Data Stream

Wang

Yang

Qiu

et al. 2019

Massive data are generated and collected by devices in the industrial Internet of Things. Data sources would encrypt the data and send them to the data center through the gateway. For some supervision purpose, the gateway needs to observe the encrypted data stream and label the suspicious data. Instead of decrypting ciphertext at the gateway, which is not efficient, this paper presents a Φ-searchable functional encryption scheme that supports inner product evaluations on encrypted data. Based on this scheme, an approach enabling various queries on the encrypted industrial data stream is proposed. The adaptive security of our proposed underlying functional encryption scheme can be proven under general subgroup decision assumptions, and our scheme has the smaller public key, the smaller secret key, and the smaller ciphertext size compared to the related schemes. In addition, the experimental results show that our proposed scheme is efficient. Especially for the gateway, querying on the encrypted data only needs less than 20ms, which is practical for industrial data stream auditing scenario.

“…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 [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Efficient Attribute-Based Encryption with Privacy-Preserving Key Generation and Its Application in Industrial Cloud

Song

Wang

Wei

et al. 2019

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.