Consortium Blockchain-Based Malware Detection in Mobile Devices

Gu, Jun; Sun, Binglin; Du, Xiaojiang; Wang, Jun; Zhuang, Yi; Wang, Ziwang

doi:10.1109/access.2018.2805783

Cited by 151 publications

(68 citation statements)

References 26 publications

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“…In the Internet of Things devices, attackers seek to exfiltrate the data of IoT devices by using the malicious codes in malware, especially on the open source Android platform. By utilizing statistical analysis method, Gu et al [46] introduced a malware detection system based on the consortium Blockchain, named CB-MDEE, which is composed of detecting consortium chain by test members and public chain by users. The CB-MDEE system adopts a fuzzy comparison method and multiple marking functions In order to reduce the false-positive rate and improve the detection ability of malware variants.…”

Section: E Internet Of Things Devicesmentioning

confidence: 99%

Blockchain Technologies for the Internet of Things: Research Issues and Challenges

Ferrag

Derdour

Mukherjee

et al. 2019

IEEE Internet Things J.

568

253

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This paper presents a comprehensive survey of the existing blockchain protocols for the Internet of Things (IoT) networks. We start by describing the blockchains and summarizing the existing surveys that deal with blockchain technologies. Then, we provide an overview of the application domains of blockchain technologies in IoT, e.g, Internet of Vehicles, Internet of Energy, Internet of Cloud, Fog computing, etc. Moreover, we provide a classification of threat models, which are considered by blockchain protocols in IoT networks, into five main categories, namely, identity-based attacks, manipulationbased attacks, cryptanalytic attacks, reputation-based attacks, and service-based attacks. In addition, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods towards secure and privacy-preserving blockchain technologies with respect to the blockchain model, specific security goals, performance, limitations, computation complexity, and communication overhead. Based on the current survey, we highlight open research challenges and discuss possible future research directions in the blockchain technologies for IoT.

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Section: E Internet Of Things Devicesmentioning

confidence: 99%

Blockchain Technologies for the Internet of Things: Research Issues and Challenges

Ferrag

Derdour

Mukherjee

et al. 2019

IEEE Internet Things J.

568

253

View full text Add to dashboard Cite

show abstract

“…However, the success of the proposed approach depends on the knowledge of the operations. According to which, the network governing equations can be calculated based on two frequencies, f 1 and f 2 , of vehicle slots for operations defined in (1). Considering that the vehicles operate in a Gaussian mode, the two frequencies for network and blockchain operations can be given as…”

Section: Global Authentication Ch Selection To Allow Necessary Connecmentioning

confidence: 99%

“…Blockchain enables shared access to information which is broadcasted across a network based on the trust of its participants [1]. Industries aiming at services for the Internet of Vehicles (IoV) consider blockchain as a leading technology for handling managerial as well as transmission aspects of vehicles [2].…”

Section: Introductionmentioning

confidence: 99%

An Energy-Efficient Transaction Model for the Blockchain-Enabled Internet of Vehicles (IoV)

Sharma

2019

IEEE Commun. Lett.

116

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The blockchain is a safe, reliable and innovative mechanism for managing numerous vehicles seeking connectivity. However, following the principles of the blockchain, the number of transactions required to update ledgers pose serious issues for vehicles as these may consume the maximum available energy. To resolve this, an efficient model is presented in this letter which is capable of handling the energy demands of the blockchainenabled Internet of Vehicles (IoV) by optimally controlling the number of transactions through distributed clustering. Numerical results suggest that the proposed approach is 40.16% better in terms of energy conservation and 82.06% better in terms of the number of transactions required to share the entire blockchaindata compared with the traditional blockchain.

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“…To obtain microcode update, a device sends its request using a blockchain on a peer‐to‐peer decentralized manner. Gu et al proposed “CB‐MDEE,” which is a framework based on blockchain; it is used to detect malware in mobile devices. The framework is based on fuzzy logic in the purpose to mitigate the false‐positive ratio and improve the detection of malware.…”

Section: Related Workmentioning

confidence: 99%

A blockchain‐based framework to secure vehicular social networks

Yahiatene

Rachedi

Riahla

et al. 2019

Trans Emerging Tel Tech

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Vehicular social network is emerging as a new promising concept, combining two types of network paradigms, namely, vehicular networks and social networks. In order to manage efficiently the security and the control of the network, this paper proposes a new framework based on the emerging concepts of software-defined vehicular network (SDVN) and blockchain. Using the SDVN makes the network more programmable, virtualized, and partitionable. However, on the other hand, it also creates a well-known vulnerability of a single point of failure. Hence, we propose to introduce the blockchain paradigm that will enable the certification of transactions and ensure data anonymity in a fully distributed manner. To this end, three levels of controllers are needed: a principal controller (PC), roadside units (RSUs), and a local controller. In order to dynamically select miners, a distributed miners connected dominating set algorithm (DM-CDS) has been proposed. The DM-CDS is a single-phase distributed algorithm that supports a dynamic topology based on a trust model and some other network parameters, such as the connectivity degree, the average link quality indicator, and the rank. The performance of the proposed DM-CDS is evaluated throughout multiple scenarios using different parameters, such as trust metric, node density, node mobility, and radio range. The obtained results highlight the importance of such proposed architecture, especially in terms of number of required miners. For instance, when the density of nodes increases, the number of selected miners increases similarly to when the network length increases. The node mobility impacts also on the stability of the selected miners, in terms of withdrawing and joining, showing a variation between 0% and 10%.The trust metric has also an important impact on the selection of miners, as only nodes with a higher trust level are selected to endorse the roles of miners.Trans Emerging Tel Tech. 2019;30:e3650.wileyonlinelibrary.com/journal/ett

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Consortium Blockchain-Based Malware Detection in Mobile Devices

Cited by 151 publications

References 26 publications

Blockchain Technologies for the Internet of Things: Research Issues and Challenges

Blockchain Technologies for the Internet of Things: Research Issues and Challenges

An Energy-Efficient Transaction Model for the Blockchain-Enabled Internet of Vehicles (IoV)

A blockchain‐based framework to secure vehicular social networks

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