scholarly journals A Provable Semi-Outsourcing Privacy Preserving Scheme for Data Transmission From IoT Devices

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 87169-87177
Author(s):  
Xiaoshuai Zhang ◽  
Chao Liu ◽  
Stefan Poslad ◽  
Kok Keong Chai
Keyword(s):  
Data Transmission ◽  
Privacy Preserving ◽  
Iot Devices

scholarly journals An Optimal Multilevel Encryption Technique for Securing the Data Transmission in IoT

2020 ◽  
Vol 9 (3) ◽  
pp. 1239-1242
Keyword(s):  
Internet Of Things ◽  
Elliptic Curve ◽  
Data Transmission ◽  
Data Security ◽  
Elliptic Curve Cryptography ◽  
Daily Life ◽  
Secret Message ◽  
Critical Component ◽  
Iot Applications ◽  
Iot Devices

Internet of Things(IoT) is playing a pivotal role in our daily life as well as in various fields like Health, agriculture, industries etc. In the go, the data in the various IoT applications will be easily available to the physical dominion and thus the process of ensuringthe security of the data will be a major concern. For the extensive implementation of the numerous applications of IoT , the data security is a critical component. In our work, we have developed an encryption technique to secure the data of IoT. With the help of Merkle-Hellman encryption the data collected from the various IoT devices are first of all encrypted and then the secret message is generated with the help of Elliptic Curve Cryptography.

Privacy-preserving aware data transmission for IoT-based e-health

2019 ◽  
Vol 162 ◽  
pp. 106866 ◽  
Author(s):  
Rihab Boussada ◽  
Balkis Hamdane ◽  
Mohamed Elhoucine Elhdhili ◽  
Leila Azouz Saidane
Keyword(s):  
Data Transmission ◽  
Privacy Preserving

scholarly journals The OLYMPUS Architecture—Oblivious Identity Management for Private User-Friendly Services

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 945 ◽  
Author(s):  
Rafael Torres Moreno ◽  
Jorge Bernal Bernabe ◽  
Jesús García Rodríguez ◽  
Tore Kasper Frederiksen ◽  
Michael Stausholm ◽  
...  
Keyword(s):  
Identity Management ◽  
Service Providers ◽  
Single Point ◽  
Building Blocks ◽  
Privacy Preserving ◽  
Privacy And Security ◽  
Iot Devices ◽  
Eu Project ◽  
Cryptographic Techniques ◽  
Identity Provider

Privacy enhancing technologies (PETs) allow to achieve user’s transactions unlinkability across different online Service Providers. However, current PETs fail to guarantee unlinkability against the Identity Provider (IdP), which becomes a single point of failure in terms of privacy and security, and therefore, might impersonate its users. To address this issue, OLYMPUS EU project establishes an interoperable framework of technologies for a distributed privacy-preserving identity management based on cryptographic techniques that can be applied both to online and offline scenarios. Namely, distributed cryptographic techniques based on threshold cryptography are used to split up the role of the Identity Provider (IdP) into several authorities so that a single entity is not able to impersonate or track its users. The architecture leverages PET technologies, such as distributed threshold-based signatures and privacy attribute-based credentials (p-ABC), so that the signed tokens and the ABC credentials are managed in a distributed way by several IdPs. This paper describes the Olympus architecture, including its associated requirements, the main building blocks and processes, as well as the associated use cases. In addition, the paper shows how the Olympus oblivious architecture can be used to achieve privacy-preserving M2M offline transactions between IoT devices.

scholarly journals Toward Blockchain-Enabled Privacy-Preserving Data Transmission in Cluster-Based Vehicular Networks

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1358 ◽  
Author(s):  
Gyanendra Prasad Joshi ◽  
Eswaran Perumal ◽  
K. Shankar ◽  
Usman Tariq ◽  
Tariq Ahmad ◽  
...  
Keyword(s):  
Data Transmission ◽  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Privacy Preserving ◽  
Transportation Systems ◽  
Security And Privacy ◽  
Driving Safety ◽  
Delivery Ratio ◽  
Blockchain Technology ◽  
On The Road

In recent times, vehicular ad hoc networks (VANET) have become a core part of intelligent transportation systems (ITSs), which aim to achieve continual Internet connectivity among vehicles on the road. The VANET has been used to improve driving safety and construct an ITS in modern cities. However, owing to the wireless characteristics, the message transmitted through the network can be observed, altered, or forged. Since driving safety is a major part of VANET, the security and privacy of these messages must be preserved. Therefore, this paper introduces an efficient privacy-preserving data transmission architecture that makes use of blockchain technology in cluster-based VANET. The cluster-based VANET architecture is used to achieve load balancing and minimize overhead in the network, where the clustering process is performed using the rainfall optimization algorithm (ROA). The ROA-based clustering with blockchain-based data transmission, called a ROAC-B technique, initially clusters the vehicles, and communication takes place via blockchain technology. A sequence of experiments was conducted to ensure the superiority of the ROAC-B technique, and several aspects of the results were considered. The simulation outcome showed that the ROAC-B technique is superior to other techniques in terms of packet delivery ratio (PDR), end to end (ETE) delay, throughput, and cluster size.

scholarly journals Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices

2020 ◽  
pp. 1-1 ◽  
Author(s):  
Yang Zhao ◽  
Jun Zhao ◽  
Linshan Jiang ◽  
Rui Tan ◽  
Dusit Niyato ◽  
...  
Keyword(s):  
Privacy Preserving ◽  
Iot Devices

scholarly journals Privacy-Preserving Data Aggregation against False Data Injection Attacks in Fog Computing

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2659 ◽  
Author(s):  
Yinghui Zhang ◽  
Jiangfan Zhao ◽  
Dong Zheng ◽  
Kaixin Deng ◽  
Fangyuan Ren ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Aggregation ◽  
Homomorphic Encryption ◽  
Fog Computing ◽  
Cloud Service ◽  
Privacy Preserving ◽  
Location Awareness ◽  
False Data Injection ◽  
Injection Attacks ◽  
Iot Devices

As an extension of cloud computing, fog computing has received more attention in recent years. It can solve problems such as high latency, lack of support for mobility and location awareness in cloud computing. In the Internet of Things (IoT), a series of IoT devices can be connected to the fog nodes that assist a cloud service center to store and process a part of data in advance. Not only can it reduce the pressure of processing data, but also improve the real-time and service quality. However, data processing at fog nodes suffers from many challenging issues, such as false data injection attacks, data modification attacks, and IoT devices’ privacy violation. In this paper, based on the Paillier homomorphic encryption scheme, we use blinding factors to design a privacy-preserving data aggregation scheme in fog computing. No matter whether the fog node and the cloud control center are honest or not, the proposed scheme ensures that the injection data is from legal IoT devices and is not modified and leaked. The proposed scheme also has fault tolerance, which means that the collection of data from other devices will not be affected even if certain fog devices fail to work. In addition, security analysis and performance evaluation indicate the proposed scheme is secure and efficient.

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