Toward Secure Data Sharing for the IoT devices with limited resources: A Smart Contract–Based Quality-Driven Incentive Mechanism

2022 ◽  
pp. 1-1
Author(s):  
Chi Zhang ◽  
Tao Shen ◽  
Fenhua Bai
Keyword(s):  
Data Sharing ◽  
Incentive Mechanism ◽  
Limited Resources ◽  
Smart Contract ◽  
Secure Data ◽  
Iot Devices

scholarly journals To Delay Instantiation of a Smart Contract to Save Calculation Resources in IoT

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Hong Su ◽  
Bing Guo ◽  
Yan Shen ◽  
Zhen Zhang ◽  
Chaoxia Qin
Keyword(s):  
Life Cycle ◽  
Power Supplies ◽  
Limited Resources ◽  
Smart Contracts ◽  
Qualitative Comparison ◽  
Smart Contract ◽  
Limited Power ◽  
Iot Devices

Smart contracts are required to be instantiated in the predeployed stage, which consumes computation resources from then on. It is a big waste in the blockchain whose nodes are composed of IoT devices, as those devices often have limited resources (such as limited power supplies or a limited number of processes to run). Meanwhile, IoT devices are heterogeneous and different smart contracts are required. If those smart contracts are instantiated previously, numerous meaningless addresses are required. In this paper, we propose to delay the instantiation of a smart contract when used and terminate it when not used, which is similar to the life cycle of a variable. Then, a new kind of variable (the wrapping variable) is used to hide details of the instantiation and the address. The smart contract is instantiated in the construction function of the wrapping variable, or even it is delayed to the time when there are requests for it. The smart contract terminates when the variable is out of its scope. Then, different instantiation methods are proposed. Finally, we perform the qualitative comparison between the proposed approach and the predeployment method, and it demonstrates that the proposed methods optimize the life cycle of the smart contract and save calculation resources.

scholarly journals Blockchain-Empowered Mobile Edge Intelligence, Machine Learning and Secure Data Sharing

2021 ◽  
Author(s):  
Yao Du ◽  
Shuxiao Miao ◽  
Zitian Tong ◽  
Victoria Lemieux ◽  
Zehua Wang
Keyword(s):  
Machine Learning ◽  
Data Sharing ◽  
Research Field ◽  
Edge Computing ◽  
Training Data ◽  
Learning Approaches ◽  
Mobile Edge Computing ◽  
User Privacy ◽  
Secure Data ◽  
Iot Devices

Driven by recent advancements in machine learning, mobile edge computing (MEC) and the Internet of things (IoT), artificial intelligence (AI) has become an emerging technology. Traditional machine learning approaches require the training data to be collected and processed in centralized servers. With the advent of new decentralized machine learning approaches and mobile edge computing, the IoT on-device data training has now become possible. To realize AI at the edge of the network, IoT devices can offload training tasks to MEC servers. However, those distributed frameworks of edge intelligence also introduce some new challenges, such as user privacy and data security. To handle these problems, blockchain has been considered as a promising solution. As a distributed smart ledger, blockchain is renowned for high scalability, privacy-preserving, and decentralization. This technology is also featured with automated script execution and immutable data records in a trusted manner. In recent years, as quantum computers become more and more promising, blockchain is also facing potential threats from quantum algorithms. In this chapter, we provide an overview of the current state-of-the-art in these cutting-edge technologies by summarizing the available literature in the research field of blockchain-based MEC, machine learning, secure data sharing, and basic introduction of post-quantum blockchain. We also discuss the real-world use cases and outline the challenges of blockchain-empowered intelligence.

scholarly journals Survey on secure protocols for data sharing through edge of cloud assisted internet of things

2018 ◽  
Vol 7 (2.7) ◽  
pp. 92 ◽  
Author(s):  
K Sai Prasanthi ◽  
K V.Daya Sagar
Keyword(s):  
Internet Of Things ◽  
Data Sharing ◽  
Data Flow ◽  
Huge Amount ◽  
Secure Data ◽  
Secure Protocols ◽  
Iot Devices

Nowadays Internet of Things (IoT) is the trending topic where we go. IoT is included in almost every device surrounded by us where valuable information is shared over the network to store it in the cloud or to transfer as a message alert to an individual. IoT devices generate a huge amount of data but only caring information is required and for that analytics needs to be performed. Analytics are reaching outside of the traditional datacenter towards the edge, where the IoT data is generated. So, here in this paper, the importance of secure data sharing over a network, generated by IoT devices is described and along with that the data flow between IoT and edge server is discussed, and the requirement of edge analytics is focused.

Blockchain-Empowered Big Data Sharing for Internet of Things

2021 ◽  
Vol 18 (1) ◽  
pp. 58-69
Author(s):  
Ting Cai ◽  
Yuxin Wu ◽  
Hui Lin ◽  
Yu Cai
Keyword(s):  
Internet Of Things ◽  
Social Welfare ◽  
Data Sharing ◽  
Large Scale ◽  
Data Control ◽  
Main Challenge ◽  
The Social ◽  
Secure Data ◽  
Iot Devices ◽  
Control And Management

A recent study predicts that by 2025, up to 75 billion internet of things (IoT) devices will be connected to the internet, in which data sharing is increasingly needed by massive IoT applications as a major driver of the IoT market. However, how to meet the interests of all participants in complex multi-party interactive data sharing while providing secure data control and management is the main challenge in building an IoT data sharing ecosystem. In this article, the authors propose a blockchain-empowered data sharing architecture that supports secure data monitoring and manageability in complex multi-party interactions of IoT systems. First, to build trust among different data sharing parties, the authors apply blockchain technologies to IoT data sharing. In particular, on-chain/off-chain collaboration and sharding consensus process are used to improve the efficiency and scalability of the large-scale blockchain-empowered data sharing systems. In order to encourage IoT parties to actively participate in the construction of shared ecology, the authors use an iterative double auction mechanism in the proposed architecture to maximize the social welfare of all parties as a case-study. Finally, simulation results show that the proposed incentive algorithm can optimize data allocations for each party and maximize the social welfare while protecting the privacy of all parties.

scholarly journals Secure data sharing for mobile cloud computing using RSA

2021 ◽  
Vol 1055 (1) ◽  
pp. 012108
Author(s):  
M Arumugam ◽  
S Deepa ◽  
G Arun ◽  
P Sathishkumar ◽  
K Jeevanantham
Keyword(s):  
Cloud Computing ◽  
Data Sharing ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Secure Data

scholarly journals Next Generation of SDN in Cloud-Fog for 5G and Beyond-Enabled Applications: Opportunities and Challenges

Network ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 28-49
Author(s):  
Ehsan Ahvar ◽  
Shohreh Ahvar ◽  
Syed Mohsan Raza ◽  
Jose Manuel Sanchez Vilchez ◽  
Gyu Myoung Lee
Keyword(s):  
Internet Of Things ◽  
Data Sharing ◽  
Mobile Networks ◽  
The Other ◽  
The Internet ◽  
Hybrid Cloud ◽  
Next Generation ◽  
Delay Constraints ◽  
Mission Critical ◽  
Iot Devices

In recent years, the number of objects connected to the internet have significantly increased. Increasing the number of connected devices to the internet is transforming today’s Internet of Things (IoT) into massive IoT of the future. It is predicted that, in a few years, a high communication and computation capacity will be required to meet the demands of massive IoT devices and applications requiring data sharing and processing. 5G and beyond mobile networks are expected to fulfill a part of these requirements by providing a data rate of up to terabits per second. It will be a key enabler to support massive IoT and emerging mission critical applications with strict delay constraints. On the other hand, the next generation of software-defined networking (SDN) with emerging cloudrelated technologies (e.g., fog and edge computing) can play an important role in supporting and implementing the above-mentioned applications. This paper sets out the potential opportunities and important challenges that must be addressed in considering options for using SDN in hybrid cloud-fog systems to support 5G and beyond-enabled applications.

Blockchain Empowered Asynchronous Federated Learning for Secure Data Sharing in Internet of Vehicles

2020 ◽  
Vol 69 (4) ◽  
pp. 4298-4311 ◽  
Author(s):  
Yunlong Lu ◽  
Xiaohong Huang ◽  
Ke Zhang ◽  
Sabita Maharjan ◽  
Yan Zhang
Keyword(s):  
Data Sharing ◽  
Internet Of Vehicles ◽  
Secure Data

scholarly journals A Proximal Algorithm for Fork-Choice in Distributed Ledger Technology for Context-Based Clustering on Edge Computing

2020 ◽  
Vol 2 (1) ◽  
pp. 92
Author(s):  
Rahim Rahmani ◽  
Ramin Firouzi ◽  
Sachiko Lim ◽  
Mahbub Alam
Keyword(s):  
Large Scale ◽  
Cluster Head ◽  
Edge Computing ◽  
Computing Technology ◽  
Proximal Algorithm ◽  
Data Intensive ◽  
Distributed Ledger ◽  
Smart Contract ◽  
Distributed Ledger Technology ◽  
Iot Devices

The major challenges of operating data-intensive of Distributed Ledger Technology (DLT) are (1) to reach consensus on the main chain as a set of validators cast public votes to decide on which blocks to finalize and (2) scalability on how to increase the number of chains which will be running in parallel. In this paper, we introduce a new proximal algorithm that scales DLT in a large-scale Internet of Things (IoT) devices network. We discuss how the algorithm benefits the integrating DLT in IoT by using edge computing technology, taking the scalability and heterogeneous capability of IoT devices into consideration. IoT devices are clustered dynamically into groups based on proximity context information. A cluster head is used to bridge the IoT devices with the DLT network where a smart contract is deployed. In this way, the security of the IoT is improved and the scalability and latency are solved. We elaborate on our mechanism and discuss issues that should be considered and implemented when using the proposed algorithm, we even show how it behaves with varying parameters like latency or when clustering.

Sign in / Sign up

Export Citation Format

Share Document