Law as a service (LaaS): Enabling legal protection over a blockchain network

Wasim, Muhammad; Ibrahim, Abdallah Ali Zainelabden Abdallah; Bouvry, Pascal; Limba, Tadas

doi:10.1109/honet.2017.8102214

Cited by 11 publications

(4 citation statements)

References 8 publications

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“…In domestic and international research, according to the needs of each application, scholars have proposed their double-chain structure. To solve the characteristics of the single-chain structure without supervision and legal protection [23], G. Wu et al [24] proposed a double-chain structure of a supervisory blockchain and transaction blockchain, to separate supervision and transaction. C. Xie et al [25] proposed a dual-chain structure of a transaction blockchain and data blockchain for the blockchain-based tracking of agricultural products, which solved the security problem and ensured that the data would not be maliciously tampered with or destroyed.…”

Section: Research On Data Storage Architecture Of Blockchainsmentioning

confidence: 99%

A Blockchain Solution for Remote Sensing Data Management Model

Zou,

Yu,

Bao

2023

Applied Sciences

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A large number of raw data collected by satellites are processed by the production chain to obtain a large number of product data, of which the secure exchange and storage is of interest to researchers in the field of remote sensing information science. Authentic, secure data provide a critical foundation for data analysis and decision-making. Traditional centralized cloud computing systems are vulnerable to attack and, once the central server is successfully attacked, all data will be lost. Distributed ledger technology (DLT) is an innovative computer technology that can ensure information security and traceability, is tamper-proof, and can be applied to the field of remote sensing. Although there are many advantages to using DLT in remote sensing applications, there are some obstacles and limitations to its application. Remote sensing data have the characteristics of a large data volume, a spatiotemporal nature, global scale, and so on, and it is difficult to store and interconnect remote sensing data in the blockchain. To address these issues, this paper proposes a trustworthy and decentralized system using blockchain technology. The novelty of this paper is the proposal of a multi-level blockchain architecture in which the system collects remote sensing data and stores them in the Interplanetary File System (IPFS) network; after generating the IPFS hash, the network rehashes the value again and uploads it on the Ethereum chain for public query. The distributed data storage improves data security, supports the secure exchange of information, and improves the efficiency of data management.

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Section: Research On Data Storage Architecture Of Blockchainsmentioning

confidence: 99%

A Blockchain Solution for Remote Sensing Data Management Model

Zou,

Yu,

Bao

2023

Applied Sciences

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“…Some of these proposals suggested that container-based monitoring can provide a real-time mechanism to record and log the data events in cloud ecosystem inline with the data privacy regulations [13]. Containerbased monitoring can also enforce controls and policies defined by organisations (such as GDPR) [27,28].…”

Section: Related Workmentioning

confidence: 99%

Compliance Checking of Cloud Providers: Design and Implementation

Barati

Adu-Duodu

Rana

et al. 2023

Distrib. Ledger Technol.

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The recognition of capabilities supplied by cloud systems is presently growing up. Collecting or sharing healthcare data and sensitive information especially during Covid-19 pandemic has motivated organizations and enterprises to leverage the upsides coming from cloud-based applications. However, the privacy of electronic data in such applications remains a significant challenge for cloud vendors to adapt their solutions with existing privacy legislation standards such as general data protection regulation (GDPR). This paper, first, proposes a formal model and verification for data usage requests of providers in a cloud composite service using a model checking tool. A cloud pharmacy scenario is presented to illustrate the connectivity of providers in the composite service and the stream of their requests for both collection and movement of patient data. A set of verification is, then, undertaken over the pharmacy service in accordance with three significant GDPR obligations, namely user consent, data access and data transfer. Following that, the paper designs and implements a cloud container virtualization based on the verified formal model realising GDPR requirements. The container makes use of some enforcement smart contracts to only proceed the providers’ requests, which are compliant with GDPR. Finally, several experiments are provided to investigate the performance of our approach in terms of time, memory and cost.

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“…Plenty of similar integration solutions were proposed to enhance stand-alone ML or BC systems. Objectives for integrating ML and BC may include intrusion detection [31,32,33,34], monitoring [35,36,37], optimization [38,39,40], price prediction [41,42,43,44], and security [45,46,47,48,49]. However, few previous works investigated the utilization of ML to optimize the classical mining (i.e.…”

Section: B Blockchain and Machine Learningmentioning

confidence: 99%

Machine Learning for Alternative Mining in PoW-based Blockchains: Theory, Implications and Applications

Baniata¹,

Prodan²,

Kertész³

2022

Preprint

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<p>Blockchain (BC) technology provides a secure distributed transactional database, that can enhance the security and privacy of decentralized systems and applications, e.g. distributed identity, supply chain and Internet of Things (IoT). The most known secure consensus mechanism for permissionless BCs is the Proof-of-Wok (PoW) algorithm. Many argue that the fastest approach to mine new blocks in PoW-based BC networks (although too energy consuming) is Brute-forcing the nonce. In this paper, we demonstrate how a well-trained Machine Learning (ML) model can find more accurate initial nonce values for this problem aiming to decrease the total energy consumption. We attempt to identify linear relationships between inputs and outputs of the classical mining processes, which typically use pure Brute-force techniques to solve the problem. Then, we integrate two ML models, namely SGDRegressor and LinearRegressor with PolynomialFeatures, into a classical mining method to predict the solution. For this, we use more than 780k+ real Bitcoin blocks for training and testing. We mathematically formalize our analysis and propose equations to predict and score the total enhancement, for any ML model deployment, compared to classical mining. We experimentally prove that our method can mine faster than the classical method. Furthermore, we discuss the implications on the node level and the network level, including the allowance for taking over the system by controlling a portion of only 35.5% out of the total computational power of the network. Finally, we apply our method in an integrated IoT-Fog-Blockchain system to enhance the fairness among participating miners.</p>

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Law as a service (LaaS): Enabling legal protection over a blockchain network

Cited by 11 publications

References 8 publications

A Blockchain Solution for Remote Sensing Data Management Model

A Blockchain Solution for Remote Sensing Data Management Model

Compliance Checking of Cloud Providers: Design and Implementation

Machine Learning for Alternative Mining in PoW-based Blockchains: Theory, Implications and Applications

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