Blockchain-Enabled Decentralized Trust Management and Secure Usage Control of IoT Big Data

Ma, Zhiliang; Wang, Lingyun; Xiaochang, Wang; Wang, Zhen; Zhao, Wenshuo

doi:10.1109/jiot.2019.2960526

Cited by 92 publications

(39 citation statements)

References 28 publications

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“…The aim is to attain the best configuration with input transactions and success rates as input parameters to the GA algorithm. The IoT data management and its traditional characteristics have been considered in [ 37 ]. The research proposes a permissioned blockchain-based decentralized trust management (BlockBDM) in order to address the security and trust problems of IoT big data management.…”

Section: Related Workmentioning

confidence: 99%

Multi-Layer Blockchain-Based Security Architecture for Internet of Things

Pajooh

Rashid

Alam

et al. 2021

Sensors

100

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The proliferation of smart devices in the Internet of Things (IoT) networks creates significant security challenges for the communications between such devices. Blockchain is a decentralized and distributed technology that can potentially tackle the security problems within the 5G-enabled IoT networks. This paper proposes a Multi layer Blockchain Security model to protect IoT networks while simplifying the implementation. The concept of clustering is utilized in order to facilitate the multi-layer architecture. The K-unknown clusters are defined within the IoT network by applying techniques that utillize a hybrid Evolutionary Computation Algorithm while using Simulated Annealing and Genetic Algorithms. The chosen cluster heads are responsible for local authentication and authorization. Local private blockchain implementation facilitates communications between the cluster heads and relevant base stations. Such a blockchain enhances credibility assurance and security while also providing a network authentication mechanism. The open-source Hyperledger Fabric Blockchain platform is deployed for the proposed model development. Base stations adopt a global blockchain approach to communicate with each other securely. The simulation results demonstrate that the proposed clustering algorithm performs well when compared to the earlier reported approaches. The proposed lightweight blockchain model is also shown to be better suited to balance network latency and throughput as compared to a traditional global blockchain.

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Section: Related Workmentioning

confidence: 99%

Multi-Layer Blockchain-Based Security Architecture for Internet of Things

Pajooh

Rashid

Alam

et al. 2021

Sensors

100

View full text Add to dashboard Cite

show abstract

“…In this regard, research on blockchain-based encryption has been conducted [133][134][135][136]. Trust relationships must be established between disparate entities in the IoT ecosystem [137]. An analysis on the combination of blockchain and trust evaluation technologies has been conducted accordingly [138,139].…”

Section: Keyword Clustering and Evolution Of Research On Iotmentioning

confidence: 99%

Current Research Trends in IoT Security: A Systematic Mapping Study

Lee

2021

Mobile Information Systems

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The smart mobile Internet-of-things (IoT) network lays the foundation of the fourth industrial revolution, the era of hyperconnectivity, hyperintelligence, and hyperconvergence. As this revolution gains momentum, the security of smart mobile IoT networks becomes an essential research topic. This study aimed to provide comprehensive insights on IoT security. To this end, we conducted a systematic mapping study of the literature to identify evolving trends in IoT security and determine research subjects. We reviewed the literature from January 2009 to August 2020 to identify influential researchers and trends of keywords. We additionally performed structural topic modeling to identify current research topics and the most promising ones via topic trend estimation. We synthesized and interpreted the results of the systematic mapping study to devise future research directions. The results obtained from this study are useful to understand current trends in IoT security and provide insights into research and development of IoT security.

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“…However large scale IoT data has data missing problems hence data recovery is an important process that is not investigated in this paper. In [28] authors addressed the problem of trust and security in IoT environment. For that, this author proposed blockchain based decentralized trust management and secure control mechanism for IoT big data.…”

Section: Literature Reviewmentioning

confidence: 99%

Centralization of Big Data Using Distributed Computing Approach in IoT

Sawiris¹,

El-Gaber²,

Abdel-Fattah³

2021

IJIES

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Centralized big data is an emerging field that manages information in one common repository. Currently, Internet of Things (IoT) devices are increasing massively for sensing and transmitting data to the big data environment. This information is sensitive and easily traced by attackers due to the centralized data management. To address the security and privacy issues and avoid the system in a single point of failure, in this paper the researchers proposed a new model, namely, BOBS CRABID i.e. Blockchain Based Secure Centralized Big Data model using distributed computing approach. In big data, Hadoop MapReduce is one of the distributed computing approaches which handles all information in a distributed manner. The BOBS CRABID model is designed by three ideas as Multi-Factor authentication, IoT Devices Data Collection and Processing, and Optics based MapReduce for Data Clustering. In multi-factor authentication, a lightweight camellia key generation algorithm (LCKGA) is used for their authenticating all devices based on ID, IP address, MAC and PUF. These credentials are saved in Blockchain Security Entity for authentication verification. All transactions are hashed and stored in the blockchain using Keccak hash algorithm which performs better than the traditional hashing (SHA) 2. Then the researchers conducted IoT devices data collection and pre-processing using Cross Correlation and Min-Max Normalization for redundant data pruning and normalization, respectively. Finally, clustering is performed in a distributed way for optimizing the storage and scalability performance. For that MapReduce is used in which OPTICS algorithm is applied for clustering based on the data size, type of context and nature of data (sensitive or non-sensitive). In this way, data is stored in the big data environment. Experiments were conducted for the proposed BOBS CRABID model and compared with the well-known methods using Hadoop 2.7.2. The proposed BOBS-CRABID model achieves better performance in terms of throughput (increase 1500mbps), response time (reduce 150ms), energy consumption (reduce 35%), attack detection rate (increase 30%), accuracy (increase 20%), computation overhead (300 kb), and time reduce 4s).

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Blockchain-Enabled Decentralized Trust Management and Secure Usage Control of IoT Big Data

Cited by 92 publications

References 28 publications

Multi-Layer Blockchain-Based Security Architecture for Internet of Things

Multi-Layer Blockchain-Based Security Architecture for Internet of Things

Current Research Trends in IoT Security: A Systematic Mapping Study

Centralization of Big Data Using Distributed Computing Approach in IoT

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