Jianhua Peng

Bio: Jianhua Peng is an academic researcher from PLA Information Engineering University. The author has contributed to research in topics: Deep learning & Network architecture. The author has an hindex of 1, co-authored 1 publications receiving 23 citations.

An in-depth and systematic literature review on the blockchain-based approaches for cloud computing

Abstract: Cloud computing enables businesses to decrease the total costs by outsourcing their required services. Therefore, it provides a new challenge of data protection regarding reliability, integrity, and confidentiality because of outsourcing. As a result, cloud security is becoming a key differentiator and competitive edge between cloud providers. Nowadays, the use of blockchain in cloud computing is one of the most common innovations that can solve cloud computing security problems. Blockchain is a decentralized data management technology to provide security, anonymity, and data integrity without any third-party organization. This work presents a comprehensive study of cloud computing security concerns and blockchain solutions to address these concerns. Applying different filters and searching international databases, 21 articles from reputable journals are found and reviewed. We examine cloud security in three categories: data integration, trust, and privacy. The results show that blockchain provides a successful platform in this regard. However, security issues are one of the most important challenges that still need further study. The article also provides a roadmap framework for future research and action.

Blockchain-based federated learning methodologies in smart environments.

Abstract: Blockchain technology is an undeniable ledger technology that stores transactions in high-security chains of blocks. Blockchain can solve security and privacy issues in a variety of domains. With the rapid development of smart environments and complicated contracts between users and intelligent devices, federated learning (FL) is a new paradigm to improve accuracy and precision factors of data mining by supporting information privacy and security. Much sensitive information such as patient health records, safety industrial information, and banking personal information in various domains of the Internet of Things (IoT) including smart city, smart healthcare, and smart industry should be collected and gathered to train and test with high potential privacy and secured manner. Using blockchain technology to the adaption of intelligent learning can influence maintaining and sustaining information security and privacy. Finally, blockchain-based FL mechanisms are very hot topics and cut of scientific edge in data science and artificial intelligence. This research proposes a systematic study on the discussion of privacy and security in the field of blockchain-based FL methodologies on the scientific databases to provide an objective road map of the status of this issue. According to the analytical results of this research, blockchain-based FL has been grown significantly during these 5 years and blockchain technology has been used more to solve problems related to patient healthcare records, image retrieval, cancer datasets, industrial equipment, and economical information in the field of IoT applications and smart environments.