A Big Data Security Architecture Based on Blockchain and Trusted Data Cloud Center

Qin, Peng; Li, Wei; Ding, Ke

doi:10.1155/2022/7272405

Cited by 3 publications

(3 citation statements)

References 14 publications

(20 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, it failed to implement the solution using the Hyperledger fabric platform to promote high transaction security and throughput. Qin et al [15] designed blockchain and trusted data cloud centers and PairHand to increase the security of cloud data centers. This approach reduced the burden on cloud centers during data processing and increased the difficulty for illegal intruders in obtaining data by storing block mapping information to ensure the security of data storage.…”

Section: Related Workmentioning

confidence: 99%

“…The security of the data is enhanced by storing the big data in a cloud or distributed file system [12]. However, the distributed data storage system dramatically increases the burden of protection on storage nodes due to difficulties in key management [15,16]. Thus, it is important to ensure data confidentiality, which is considered a major requirement of today's systems.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the validation of various data-sharing approaches in terms of encryption time is displayed in Figure12c. The IABHE+DSNN achieved a minimum encryption time of15The validation of various data-sharing models utilizing encryption time is given in Figure13c. The prevailing data-sharing models, such as PRE + TEE, Medi-Block record, MA-RABE, and BSKM, obtained encryption time of 41.786 s, 37.786 s, 33.978 s, and 31.876 s for a key size of 256Bits, whereas IABHE+DSNN recorded minimum encryption time of 28.876 s.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Blockchain-Enabled Secure Data Sharing with Honey Encryption and DSNN-Based Key Generation

Siyal,

Long,

Asim

et al. 2024

Mathematics

View full text Add to dashboard Cite

Ensuring data confidentiality is a critical requirement for modern security systems globally. Despite the implementation of various access-control policies to enhance system security, significant threats persist due to insecure and inadequate access management. To address this, Multi-Party Authorization (MPA) systems employ multiple authorities for authorization and authentication, utilizing blockchain technology to store and access data securely, ensuring immutable and trusted audit trails. In this work, we propose a hybrid key-generation approach called the Identity and Attribute-Based Honey Encryption (IABHE) Algorithm combined with Deep Spiking Neural Network (DSNN) denoted by IABHE+DSNN for secure data sharing in a multi-party blockchain-based system. This approach incorporates various entities and multiple security functionalities to ensure data security. The data-sharing process involves several steps: initialization, authentication, initial registration, data protection, validation, and data sharing. Data protection is executed within the MapReduce framework, with data encryption performed using IABHE and key generation managed by DSNN. Experimental results demonstrate that the proposed IABHE+DSNN approach achieves a decryption time of 10.786 s, an encryption time of 15.765 s, and a key complexity of 0.887, outperforming existing methods.

show abstract

Section: Related Workmentioning

confidence: 99%