Asymmetric Consortium Blockchain and Homomorphically Polynomial-Based PIR for Secured Smart Parking Systems

Haritha, T.; Anitha, A.

doi:10.32604/cmc.2023.036278

Cited by 8 publications

(4 citation statements)

References 25 publications

(30 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By combining different types of privacy-preserving approaches, a hybrid solution can overcome the weaknesses of individual approaches by providing stronger techniques. For example, by combining blockchain with homomorphic encryption a decentralised, transparent privacy-preserving solution is presented for smart parking with minimum computation and communication overhead [2]. In this section, we discuss approaches that:…”

Section: Mixed Hybrid and Miscellaneous Approachesmentioning

confidence: 99%

See 1 more Smart Citation

A Review of Privacy Enhancement Methods for Federated Learning in Healthcare Systems

Gu,

Sabrina,

Fan

et al. 2023

IJERPH

View full text Add to dashboard Cite

Federated learning (FL) provides a distributed machine learning system that enables participants to train using local data to create a shared model by eliminating the requirement of data sharing. In healthcare systems, FL allows Medical Internet of Things (MIoT) devices and electronic health records (EHRs) to be trained locally without sending patients data to the central server. This allows healthcare decisions and diagnoses based on datasets from all participants, as well as streamlining other healthcare processes. In terms of user data privacy, this technology allows collaborative training without the need of sharing the local data with the central server. However, there are privacy challenges in FL arising from the fact that the model updates are shared between the client and the server which can be used for re-generating the client’s data, breaching privacy requirements of applications in domains like healthcare. In this paper, we have conducted a review of the literature to analyse the existing privacy and security enhancement methods proposed for FL in healthcare systems. It has been identified that the research in the domain focuses on seven techniques: Differential Privacy, Homomorphic Encryption, Blockchain, Hierarchical Approaches, Peer to Peer Sharing, Intelligence on the Edge Device, and Mixed, Hybrid and Miscellaneous Approaches. The strengths, limitations, and trade-offs of each technique were discussed, and the possible future for these seven privacy enhancement techniques for healthcare FL systems was identified.

show abstract

Section: Mixed Hybrid and Miscellaneous Approachesmentioning

confidence: 99%

“…The FL server aggregates the model weights and then sends the new model weights back to the participants. The iterated training allows each participant to build one global model collaboratively without ever sharing the data with other participants [2].…”

Section: Introductionmentioning

confidence: 99%

A Review of Privacy Enhancement Methods for Federated Learning in Healthcare Systems

Gu,

Sabrina,

Fan

et al. 2023

IJERPH

View full text Add to dashboard Cite

show abstract

“…Some people have proposed to integrate blockchain with the Internet of things and use information and communication technology. A sustainable ecosystem was created in [17], while other researchers put forward an improved asymmetric alliance blockchain, as well as a univariate polynomialbased homomorphism computing privacy information retrieval scheme, to ensure the availability and transparency of the parking lot in the privacy protection intelligent parking system [18]. It can be seen that the application of blockchain technology is extensive.…”

Section: Blockchain Technology and Its Algorithm Classificationmentioning

confidence: 99%

Research on Innovation Management of Enterprise Supply Chain Digital Platform Based on Blockchain Technology

Hou

2023

Sustainability

View full text Add to dashboard Cite

Purpose: In response to the problems of high production costs, weak comprehensive competitiveness, and incomplete capital chain in the development of enterprises in the international market, this article proposes to apply blockchain technology to the digital platform of the supply chain. By scientifically managing the digital platform, enterprises can reduce production costs and improve their capital chain. Design/methodology/approach: In this long-term economic life, theoretical science and technology are still developing, gradually forming a blockchain-based enterprise supply chain development model. The continuous research on the blockchain theory can provide more convenient services for the supply chain digital platform innovation management. Findings: This article studies the entire supply chain management process through blockchain algorithms and innovative management methods, which can enable enterprises to further develop on the digital platform of supply chain, promote the digital construction of supply chain, and ensure the sustainable development of enterprises. Originality/value: This can reduce the supply chain digital platform innovation management risk of enterprises by more than 60%, as well as reduce the cost of enterprises, which has a more far-reaching impact on the sustainable development of enterprises.

show abstract

“…The data-driven approach is the most commonly used decision-making method. Data-driven can be used for campus building facility management [10], system downtime monitoring [11], parking space allocation, and privacy protection [12], reducing the loss of manpower and resources. At the same time, data-driven decision-making can also enable correct decision-making in industry [13,14], reduce wasted costs [15], and improve O&M efficiency.…”

Section: Introductionmentioning

confidence: 99%

Purpose-Driven Evaluation of Operation and Maintenance Efficiency and Safety Based on DIKWP

Liu,

Wang,

Wang

et al. 2023

Sustainability

View full text Add to dashboard Cite

In large-scale public security equipment projects, long-term equipment operation often leads to equipment failures and other problems, so it is particularly important to choose the appropriate operation and maintenance (O&M) scheme based on the content of the equipment work orders. However, there are a variety of equipment models in the work orders; not only is the data complex, but also due to the long project cycle, there are often problems such as loss of content, which bring great challenges to the O&M work. This paper defines these problems as “3-No problems”: inconsistency, inaccuracy, and incompleteness. In this paper, an improved DIKWP model is proposed and combined with a random forest classifier to construct data graphs, information graphs, knowledge graphs, and wisdom graphs. Through the above model, the 3-No problem in equipment work orders can be solved, and the importance of each equipment model can be obtained. Eventually, combined with the purpose graph, the selection of models, the bid score calculation, and the selection of O&M schemes are carried out based on the obtained conclusion in a purpose-driven manner to achieve the evaluation of O&M efficiency and safety. Finally, an example is assumed to illustrate the application of the method in actual projects, which provides a certain reference value for the selection of an O&M scheme for large-scale equipment projects.

show abstract

Asymmetric Consortium Blockchain and Homomorphically Polynomial-Based PIR for Secured Smart Parking Systems

Cited by 8 publications

References 25 publications

A Review of Privacy Enhancement Methods for Federated Learning in Healthcare Systems

A Review of Privacy Enhancement Methods for Federated Learning in Healthcare Systems

Research on Innovation Management of Enterprise Supply Chain Digital Platform Based on Blockchain Technology

Purpose-Driven Evaluation of Operation and Maintenance Efficiency and Safety Based on DIKWP

Contact Info

Product

Resources

About