Data Protection legislation has evolved around the globe to maximize legal protection of trade secrets. However, in an online cross-jurisdiction environment of cloud computing and blockchains, it is becoming increasingly difficult to maximize retribution for trade secret misappropriation. This multidisciplinary Ph.D. research proposes a model for legal protection for trade secrets in the cloud and over blockchains. Two QoS based datasets were used for evaluation of proposed model. The prior dataset i.e., feedback from customers, was compiled using leading review websites such as Cloud Hosting Reviews, Best Cloud Computing Providers, and Cloud Storage Reviews and Ratings. The later dataset i.e., feedback from servers, was generated from Cloud brokerage architecture that was emulated using high performance computing (HPC) cluster at University of Luxembourg (HPC @ Uni.lu). The simulation runs in the stable environment i.e. when uncertainty is low, show better results of proposed model as compared to its counterparts in the field. In particular, the results have implications for enterprises that view trade secrets misappropriation as a limiting factor for acquisition of Cloud services. For legal validation of the results, questionnaires were sent to law and ICT experts. There were total of six respondents (two from the field of ICT, two from the field of law, and two from the field of ICT and Law). The sample (5 out of 6 respondents) agreed with the findings of this PhD research.

Design and Implementation of Legal Protection for Trade Secrets in Cloud Brokerage Architectures relying on Blockchains

2018

Abstract

Data Protection legislation has evolved around the globe to maximize legal protection of trade secrets. However, in an online cross-jurisdiction environment of cloud computing and blockchains, it is becoming increasingly difficult to maximize retribution for trade secret misappropriation. This multidisciplinary Ph.D. research proposes a model for legal protection for trade secrets in the cloud and over blockchains. Two QoS based datasets were used for evaluation of proposed model. The prior dataset i.e., feedback from customers, was compiled using leading review websites such as Cloud Hosting Reviews, Best Cloud Computing Providers, and Cloud Storage Reviews and Ratings. The later dataset i.e., feedback from servers, was generated from Cloud brokerage architecture that was emulated using high performance computing (HPC) cluster at University of Luxembourg (HPC @ Uni.lu). The simulation runs in the stable environment i.e. when uncertainty is low, show better results of proposed model as compared to its counterparts in the field. In particular, the results have implications for enterprises that view trade secrets misappropriation as a limiting factor for acquisition of Cloud services. For legal validation of the results, questionnaires were sent to law and ICT experts. There were total of six respondents (two from the field of ICT, two from the field of law, and two from the field of ICT and Law). The sample (5 out of 6 respondents) agreed with the findings of this PhD research.
2018
it
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/346634
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