Lightweight Ring Signatures for Decentralized Privacy-preserving Transactions

Malina, Lukáš; Hajný, Jan; Dzurenda, Petr; Ricci, Sara

doi:10.5220/0006890506920697

Cited by 10 publications

(11 citation statements)

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“…Privacy in the blockchain is a major issue where transactions or users identity should be untraceable and un-linkable. For the purpose of anonymity, the framework uses a lightweight digital ring signature [ 45 ]. The basic idea behind the ring signature (see Figure 17 ) is mixing the users signature with other members, and no one in the network can identify which member signed the message.…”

Section: Our Systemmentioning

confidence: 99%

Internet of Things Based Blockchain for Temperature Monitoring and Counterfeit Pharmaceutical Prevention

Singh

Dwivedi

Srivastava

2020

Sensors

138

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The top priority of today’s healthcare system is delivering medicine directly from the manufacturer to end-user. The pharmaceutical supply chain involves some level of commingling of a collection of stakeholders such as distributors, manufacturers, wholesalers, and customers. The biggest challenge associated with this supply chain is temperature monitoring as well as counterfeit drug prevention. Many drugs and vaccines remain viable within a specific range of temperatures. If exposed beyond this temperature range, the medicine no longer works as intended. In this paper, an Internet of Things (IoT) sensor-based blockchain framework is proposed that tracks and traces drugs as they pass slowly through the entire supply chain. On the one hand, these new technologies of blockchain and IoT sensors play an essential role in supply chain management. On the other hand, they also pose new challenges of security for resource-constrained IoT devices and blockchain scalability issues to handle this IoT sensor-based information. In this paper, our primary focus is on improving classic blockchain systems to make it suitable for IoT based supply chain management, and as a secondary focus, applying these new promising technologies to enable a viable smart healthcare ecosystem through a drug supply chain.

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Section: Our Systemmentioning

confidence: 99%

Internet of Things Based Blockchain for Temperature Monitoring and Counterfeit Pharmaceutical Prevention

Singh

Dwivedi

Srivastava

2020

Sensors

138

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“…Information that has not been maintained on the user's computer or in cloud services must be moved to block chain networks. As a result, we utilize a minimal digital signature [56] technique to verify that information is not changed .In order to process IoT massive data, we require cloud servers. There is a risk, though, that it will create an issue with trustworthy third parties.…”

Section: Ai Enabled Blockchain Malware Detection Using Iot In E-health Applicationsmentioning

confidence: 99%

Block chain based Malware Detection using Machine Learning Algorithms for IoT enabled E-Health Applications

2021

International Journal For Innovative Engineering and Management

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Due to increasing digitalization and the development of new technologies such as the IoT, the application of machine learning (ML) algorithms is rapidly expanding (IoT). ML algorithms are being used in healthcare, IoT, engineering, finance, and other fields in today's digital age. However, in order to predict/solve a specific issue, all of these algorithms must be taught. There's a good chance that the training datasets have been tampered with, resulting in skewed findings. As a result, we have suggested a blockchain-based approach to protect datasets produced by IoT devices for E-Health applications in this paper. To address the aforementioned problem, the suggested blockchain-based system makes use of a private cloud. For assessment, we created a mechanism that dataset owners may use to protect their data.

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“…Normally, in group signatures any member can anonymously sign a message on behalf of the group and only the group managers/issuers are able to add users and trace or revoke users. 107 The centralized nature of the group signature makes it useful for a cooperative network, in which the group manager is a trusted party. In the ring signature, 108 which is signer-ambiguous, there is no pre-arranged group of users and no way to distribute specialized keys.…”

Section: Ring Signaturementioning

confidence: 99%

“…The larger the value of r is, the greater is the implied privacy, as the anonymous objects are identifiable with the probability greater than 1/r . 97 Manlina et al 107 proposed lightweight ring signatures to provide anonymous transactions in a constrained environment such as an IoT network. By shuffling the public keys in the ring set, the authors tried to remove any possibility of identifying the actual signer.…”

Section: Ring Signaturementioning

confidence: 99%

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An evaluation framework for privacy‐preserving solutions applicable for blockchain‐based internet‐of‐things platforms

Firoozjaei

Ghorbani

2020

Security and Privacy

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Blockchain-based applications provide many promising opportunities to overcome the challenges associated with the Internet of Things (IoT) ecosystems (eg, centralized architecture, data integrity, and reliability). In particular, blockchain technology offers many desirable features for IoT infrastructures, such as decentralization, trustworthiness, trackability, and immutability. However, while logging all transactions in a distributed blockchain ledger provides transparency, it also makes it possible to compromise user's privacy, thus posing a grand challenge to IoT architects and implementers. Over the past years, a set of solutions have been proposed for various scenarios, to address these privacy issues. In this paper, we survey these solutions, classify, and analyze their advantages and disadvantages. We also introduce an evaluation framework to evaluate the quality of the privacy-preserving based on an adjustable weighting scheme. Finally, we rate the analyzed solutions based on their privacy ranks, and hope our evaluation can shed light on the future design of privacy-preserving solutions applicable for blockchain-based IoT platforms. K E Y W O R D S blockchain-based application, internet-of-things, privacy rank, privacy-preserving 1 INTRODUCTION Blockchain-based applications have been widely employed to address issues such as intensive centralizing, scalability, security, and reliability with Internet of Things (IoT) systems. IoT systems are characterized by multi-party ecosystems, with data exchange among different devices and parties. 1 The tamper-proof, immutability, and transparency features of blockchain make members able to trace all transactions (past and present), which provides a reliable way to identify data leakages or manipulation. 2-4 The integrity of huge amounts of IoT sensory data can be assured in a blockchain-based distributed cloud from sensor to service with no need to rely on trusted third parties. 5 Data provenance tracking can be provided by programmable smart contracts, which act as the policy evaluation entities and event loggers, and allows users to check all data transfers (eg, acquired automatically from IoT devices) and usage transactions providing assurance that only transactions conforming to the contract policies are authorized and registered in the blockchain. 6 IoT system restrictions, namely resource-constrained devices, low computational power, and limited capacity and bandwidth limit blockchain-IoT applications. For this reason, different projects, such as Maru,* Riddle&Code, † IOTA, ‡ and IBM's device democracy, aim to fit blockchain to IoT platforms, to achieve interoperability, trust machine-to-machine (M2M) interaction, data integrity, and device-based permission. Maru sensor platform, developed by chain of things

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Lightweight Ring Signatures for Decentralized Privacy-preserving Transactions

Cited by 10 publications

References 0 publications

Internet of Things Based Blockchain for Temperature Monitoring and Counterfeit Pharmaceutical Prevention

Internet of Things Based Blockchain for Temperature Monitoring and Counterfeit Pharmaceutical Prevention

Block chain based Malware Detection using Machine Learning Algorithms for IoT enabled E-Health Applications

An evaluation framework for privacy‐preserving solutions applicable for blockchain‐based internet‐of‐things platforms

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