International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Data protection is about protecting information about per-sons, which is currently flowing without much control āindividuals can-not easily exercise the rights granted by the EU General Data Protection Regulation (GDPR). Individuals benefit from āfreeā services offered by companies in exchange of their data, but these companies keep their usersā data in āsilosā that impede transparency on their use and possibilities of easy interactions. The introduction of the GDPR warrants control rights to individuals and the free portability of personal data from one entity to another. However it is still beyond the individualās capability to perceive whether their data is managed in compliance with GDPR. To this regard, in this work the proposed approach consists in using decentralized mechanisms to provide transparency through distributed ledgers, data flow governance by using smart contracts and interoperability relying on semantic web technologies.
Bing Jia, Tao Zhou, Wuyungerile Li, Zhenchang Liu Ā· 5 authors
Crowd sensing is a perception mode that recruits mobile device users to complete tasks such as data collection and cloud computing. For the cloud computing platform, crowd sensing can not only enable users to collaborate to complete large-scale awareness tasks but also provide users for types, social attributes, and other information for the cloud platform. In order to improve the effectiveness of crowd sensing, many incentive mechanisms have been proposed. Common incentives are monetary reward, entertainment & gamification, social relation, and virtual credit. However, there are rare incentives based on privacy protection basically. In this paper, we proposed a mixed incentive mechanism which combined privacy protection and virtual credit called a blockchain-based location privacy protection incentive mechanism in crowd sensing networks. Its network structure can be divided into three parts which are intelligence crowd sensing networks, confusion mechanism, and blockchain. We conducted the experiments in the campus environment and the results shows that the incentive mechanism proposed in this paper has the efficacious effect in stimulating user participation.
Blockchain is considered one of the most disruptive technologies of our time. Numerous cities around the world are launching blockchain initiatives as part of the overall efforts toward shaping the urban future. However, the infancy stage of the blockchain industry leads to a severe gap between the knowledge we have and the actions urban policy makers are taking. This paper is an effort to narrow this rift. We provide a systematic literature review on concrete blockchain use cases proposed by the research community. At the macro-level, we discuss and organize use cases from 159 selected papers into nine sectors recognized as crucial for sustainable and smart urban future. At the micro-level, we identify a component-based framework and analyze the design and prototypes of blockchain systems studied in a subset of 71 papers. The high-level use case review allows us to illustrate the relationship between them and the four pillars of urban sustainability: social, economic, environmental, and governmental. The system level analysis helps us highlight interesting inconsistencies between well-known blockchain applicability decision rules and the approaches taken by the literature. We also offer two classification methodologies for blockchain use cases and elaborate on how they can be applied to stimulate cross-sector insights in the blockchain knowledge domain.
Petra Isenberg, Christoph Kinkeldey, JeanāDaniel Fekete
We contribute a visual exploration system for analyzing the behavior of individual entities exchanging Bitcoins. Bitcoin is a cryptocurrency, popular for allowing pseudonymous financial transactions. The Bitcoin blockchain is the public ledger of the Bitcoin system holding data on millions of individual transactions between pseudonymous addresses. These addresses belong to individual entities such as people, services, or enterprises. Understanding how the Bitcoin system is used, however, is difficult because it is unclear which addresses belong to the same entities. Our tool addresses this
problem by clustering addresses and displaying transaction detail for individual entities