Accountable mobile E-commerce scheme in intelligent cloud system transactions

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.

Section: Application In Industrial Cloudmentioning

confidence: 99%

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

Song

Wang

Wei

et al. 2019

“…A variety of cloud services have been deployed to store and process the big data of IIOT [1][2][3][4]. Due to the openness of public network, these cloud services suffer from a wide range of attacks [5][6][7][8]. Text-based passwords remain the dominant authentication technique for various online services and systems, because it is accessible and convenient.…”

Section: Introductionmentioning

confidence: 99%

Fingerprint Protected Password Authentication Protocol

Yang

Zhang

Guo

et al. 2019

With the rapid development of industrial Internet of things (IIOT), a variety of cloud services have been deployed to store and process the big data of IIOT. The traditional password only authentication is unable to meet the needs of security situation in IIOT. Therefore, a lot of mobile phone assisted password authentication schemes have been proposed. However, in existing schemes, the secret information is required to be stored in the user’s mobile phone. Once the phone is lost, the secret information may be obtained by the opponent, which will bring irreparable loss to the user. To address the above problems, we propose a fingerprint protected password authentication scheme which has no need to store the secret parameter in the mobile phone. When a user logs in, he uses his mobile phone to generate the private key which is used to decrypt the encrypted text generated during the registration phase. The process of generating the private key needs to enter the password and the fingerprint. When the computer interacts with the mobile phone, the user’s password will be blinded so that it can protect the user’s password from adversary’s attacks. Theoretical analysis and experimental results show that our scheme improves the security of the user’s secret. Meanwhile, our scheme can resist the opponent’s dictionary attacks, replay attacks, and phishing attack. Our scheme can reduce the storage pressure of the mobile phone and is easy to deploy.

“…With the rapid development of big data, the significance of privacy and security issues was highly regarded. A series of cryptoghraphic applications, such as fair electronic transaction [1], outsourcing data classification [2], lightweight security system of Internet of Things [3], mobile Ecommerce [4], and data mining based on homomorphic encryption, have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Improved Cryptanalysis of a Fully Homomorphic Symmetric Encryption Scheme

Wang

Ping

2019

Homomorphic encryption is widely used in the scenarios of big data and cloud computing for supporting calculations on ciphertexts without leaking plaintexts. Recently, Li et al. designed a symmetric homomorphic encryption scheme for outsourced databases. Wang et al. proposed a successful key-recovery attack on the homomorphic encryption scheme but required the adversary to know some plaintext/ciphertext pairs. In this paper, we propose a new ciphertext-only attack on the symmetric fully homomorphic encryption scheme. Our attack improves the previous Wang et al.’s attack by eliminating the assumption of known plaintext/ciphertext pairs. We show that the secret key of the user can be recovered by running lattice reduction algorithms twice. Experiments show that the attack successfully and efficiently recovers the secret key of the randomly generated instances with an overwhelming probability.