Dataset Information

Peace engineering: The contribution of blockchain systems to the e-voting process.

ABSTRACT: In recent decades, several countries have faced political tensions due to citizens' perceptions that their elections are fraudulent; some electors have even chosen not to vote because they believe that the results may be falsified. Thus, electoral fraud is a major issue. E-governance and e-voting are now being used in many countries, some of which are investigating blockchain solutions. The aim of this study is to investigate the potential contributions of blockchain technology to peace on a worldwide level by securing voting systems. Unfortunately, this technology is complex and could potentially generate conflict between actors in elections. Taking an exploratory approach, the authors chose a qualitative method to address this specific topic. Election observers and blockchain experts were interviewed to identify the technology's strengths and weaknesses. Our results emphasize the importance of trust and human factors in the voting process.

SUBMITTER: Baudier P

PROVIDER: S-EPMC7554464 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Peace engineering: The contribution of blockchain systems to the e-voting process.

Baudier Patricia P Kondrateva Galina G Ammi Chantal C Seulliet Eric E

Technological forecasting and social change 20201014

In recent decades, several countries have faced political tensions due to citizens' perceptions that their elections are fraudulent; some electors have even chosen not to vote because they believe that the results may be falsified. Thus, electoral fraud is a major issue. E-governance and e-voting are now being used in many countries, some of which are investigating blockchain solutions. The aim of this study is to investigate the potential contributions of blockchain technology to peace on a wor ...[more]

PMID: 33071364

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Project description:A lot of hard work and years of research are still needed for developing successful Blockchain (BC) applications. Although it is not yet standardized, BC technology was proven as to be an enhancement factor for security, decentralization, and reliability, leading to be successfully implemented in cryptocurrency industries. Fog computing (FC) is one of the recently emerged paradigms that needs to be improved to serve Internet of Things (IoT) environments of the future. As hundreds of projects, ideas, and systems were proposed, one can find a great R&D potential for integrating BC and FC technologies. Examples of organizations contributing to the R&D of these two technologies, and their integration, include Linux, IBM, Google, Microsoft, and others. To validate an integrated Fog-Blockchain protocol or method implementation, before the deployment phase, a suitable and accurate simulation environment is needed. Such validation should save a great deal of costs and efforts on researchers and companies adopting this integration. Current available simulation environments facilitate Fog simulation, or BC simulation, but not both. In this paper, we introduce a Fog-Blockchain simulator, namely FoBSim, with the main goal to ease the experimentation and validation of integrated Fog-Blockchain approaches. According to our proposed workflow of simulation, we implement different Consensus Algorithms (CA), different deployment options of the BC in the FC architecture, and different functionalities of the BC in the simulation. Furthermore, technical details and algorithms on the simulated integration are provided. We validate FoBSim by describing the technologies used within FoBSim, highlighting FoBSim's novelty compared to the state-of-the-art, discussing the event validity in FoBSim, and providing a clear walk-through validation. Finally, we simulate case studies, then present and analyze the obtained results, where deploying the BC network in the fog layer shows enhanced efficiency in terms of total run time and total storage cost.

Project description:BackgroundThe protection of private data is a key responsibility for research studies that collect identifiable information from study participants. Limiting the scope of data collection and preventing secondary use of the data are effective strategies for managing these risks. An ideal framework for data collection would incorporate feature engineering, a process where secondary features are derived from sensitive raw data in a secure environment without a trusted third party.ObjectiveThis study aimed to compare current approaches based on how they maintain data privacy and the practicality of their implementations. These approaches include traditional approaches that rely on trusted third parties, and cryptographic, secure hardware, and blockchain-based techniques.MethodsA set of properties were defined for evaluating each approach. A qualitative comparison was presented based on these properties. The evaluation of each approach was framed with a use case of sharing geolocation data for biomedical research.ResultsWe found that approaches that rely on a trusted third party for preserving participant privacy do not provide sufficiently strong guarantees that sensitive data will not be exposed in modern data ecosystems. Cryptographic techniques incorporate strong privacy-preserving paradigms but are appropriate only for select use cases or are currently limited because of computational complexity. Blockchain smart contracts alone are insufficient to provide data privacy because transactional data are public. Trusted execution environments (TEEs) may have hardware vulnerabilities and lack visibility into how data are processed. Hybrid approaches combining blockchain and cryptographic techniques or blockchain and TEEs provide promising frameworks for privacy preservation. For reference, we provide a software implementation where users can privately share features of their geolocation data using the hybrid approach combining blockchain with TEEs as a supplement.ConclusionsBlockchain technology and smart contracts enable the development of new privacy-preserving feature engineering methods by obviating dependence on trusted parties and providing immutable, auditable data processing workflows. The overlap between blockchain and cryptographic techniques or blockchain and secure hardware technologies are promising fields for addressing important data privacy needs. Hybrid blockchain and TEE frameworks currently provide practical tools for implementing experimental privacy-preserving applications.

Dataset Information

Peace engineering: The contribution of blockchain systems to the e-voting process.

Publications

Peace engineering: The contribution of blockchain systems to the e-voting process.

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