Privacy-Preserving Blockchain-Based Solutions in the Internet of Things

Author(s):  
Nikolaos Zapoglou ◽  
Ioannis Patsakos ◽  
George Drosatos ◽  
Konstantinos Rantos
2019 ◽  
Vol 151 ◽  
pp. 256-263 ◽  
Author(s):  
Maryline Laurent ◽  
Jean Leneutre ◽  
Sophie Chabridon ◽  
Imane Laaouane

2016 ◽  
Vol 102 ◽  
pp. 83-95 ◽  
Author(s):  
Lukas Malina ◽  
Jan Hajny ◽  
Radek Fujdiak ◽  
Jiri Hosek

2013 ◽  
Vol 427-429 ◽  
pp. 2466-2469 ◽  
Author(s):  
Ping Shui Wang

The Internet of Things is a novel paradigm in the scenario of modern wireless telecommunications. It has high impact on several aspects of everyday-life and behavior of potential users. However, it raises serious concerns over individual privacy in the new environment of smart things. In this paper, we provide for an overview on privacy preserving techniques in the Internet of Things and discuss the present problems and directions for future research.


2018 ◽  
Vol 49 ◽  
pp. 126-138 ◽  
Author(s):  
Luca Luceri ◽  
Felipe Cardoso ◽  
Michela Papandrea ◽  
Silvia Giordano ◽  
Julia Buwaya ◽  
...  

Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 103 ◽  
Author(s):  
Lin Liu ◽  
Jinshu Su ◽  
Baokang Zhao ◽  
Qiong Wang ◽  
Jinrong Chen ◽  
...  

With the fast development of the Internet of Things (IoT) technology, normal people and organizations can produce massive data every day. Due to a lack of data mining expertise and computation resources, most of them choose to use data mining services. Unfortunately, directly sending query data to the cloud may violate their privacy. In this work, we mainly consider designing a scheme that enables the cloud to provide an efficient privacy-preserving decision tree evaluation service for resource-constrained clients in the IoT. To design such a scheme, a new secure comparison protocol based on additive secret sharing technology is proposed in a two-cloud model. Then we introduce our privacy-preserving decision tree evaluation scheme which is designed by the secret sharing technology and additively homomorphic cryptosystem. In this scheme, the cloud learns nothing of the query data and classification results, and the client has no idea of the tree. Moreover, this scheme also supports offline users. Theoretical analyses and experimental results show that our scheme is very efficient. Compared with the state-of-art work, both the communication and computational overheads of the newly designed scheme are smaller when dealing with deep but sparse trees.


2017 ◽  
Vol 2017 ◽  
pp. 1-20 ◽  
Author(s):  
Jorge Bernal Bernabe ◽  
Jose L. Hernandez-Ramos ◽  
Antonio F. Skarmeta Gomez

Security and privacy concerns are becoming an important barrier for large scale adoption and deployment of the Internet of Things. To address this issue, the identity management system defined herein provides a novel holistic and privacy-preserving solution aiming to cope with heterogeneous scenarios that requires both traditional online access control and authentication, along with claim-based approach for M2M (machine to machine) interactions required in IoT. It combines a cryptographic approach for claim-based authentication using the Idemix anonymous credential system, together with classic IdM mechanisms by relying on the FIWARE IdM (Keyrock). This symbiosis endows the IdM system with advanced features such as privacy-preserving, minimal disclosure, zero-knowledge proofs, unlikability, confidentiality, pseudonymity, strong authentication, user consent, and offline M2M transactions. The IdM system has been specially tailored for the Internet of Things bearing in mind the management of both users’ and smart objects’ identity. Moreover, the IdM system has been successfully implemented, deployed, and tested in the scope of SocIoTal European research project.


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