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

Data Protection legislation has evolved around the globe to maximize legal protection of trade secrets. However, it is becoming increasingly difficult to prove trade secret violations in cloud context. Embedding legal protection as a preemptive measure could effectively reduce such burden of proof in a court of law, which can be implemented by an online broker in the cloud. The primary aim of this research was to propose a model for an online broker that embeds le-gal protection as preemptive measure to reduce burden of proof during litigation. This is a novel area of inter-disciplinary research whose body of knowledge is not yet well established. The underlying concept in the proposed model was built upon the notion of factor analysis from the discipline of unsupervised machine learning. For evaluation, two-stage procedure was implemented that showed ap-plication of legal protection as preemptive measure and subsequently, reduced burden of proof in a court of law. A real time quality of service based dataset for cloud storage providers (Carbonite, Dropbox, iBackup, JustCloud, SOS Online Backup, SugarSync, and Zip Cloud) was used for the technical evaluation. The simulation results showed better results of proposed model as compared to its counterparts in the field, which in court of law can be used as a part of evidence to reduce burden of proof. For legal validation of such conclusion, 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 that results of our model could be used in the court (or judiciary) as a part of evidence to reduce burden of proof. Theoretically, this part of research (focused on primary aim) is a pioneer effort on providing legal protection to trade secrets in the cloud. Practically, it will benefit an enterprise to negotiate contract with service providers to minimize trade secret misappropriation in the cloud.
However, for enterprise that is using decentralized architecture in the cloud e.g. blockchains, contracts could emerge towards smart contracts (an autono-mous software program running over blockchains). In this context, a well negoti-ated contract will not be a solution to minimize trade secret misappropriation. In fact, for this case it is particularly relevant to instantiate role of judiciary over a blockchain. The secondary aim of this research was to develop a model that can be implemented over the blockchain to automatically issue preliminary injunc-tion (or temporary restraining order by court of law) for the breach of contract that can potentially lead to trade secret misappropriation. This part of the re-search extended the previously proposed model by using stochastic modeling from the discipline of data science. High performance computing (HPC) cluster at University of Luxembourg (HPC @ Uni.lu) and docker (a software container platform) were used to emulate contractual environment of three service provid-ers: Redis, MongoDB, and Memcached Servers. The results showed that court in-junction(s) was issued only for Redis and MongoDB Servers. Technically, this difference could be attributed to the fact that Memcached is simply used for caching and therefore, it is less prone to breach of contract. Whereas, Redis and MongoDB as databases and message brokers are performing more complex oper-ations and are more likely to cause a breach. For legal validation of the results, questionnaires were sent to law and ICT experts. There were total of six respond-ents (two from the field of ICT, two from the field of law, and two from the field of ICT and Law). The sample (4 out of 6 respondents) disagreed “ONLY” using the results of the model by the court of law (or judiciary) to issues a preliminary injunction (or temporary restraining order) for the breach of contract. Theoreti-cally, this part of the research is a pioneer attempt for providing legal protection over the blockchain. Practically, it will benefit blockchain driven enterprises to control and stop breach of contract that can potentially lead to trade secret mis-appropriation.
In addition to above mentioned applied benefits, following list briefly presents research contributions of this multidisciplinary Ph.D. research in the domain of Law.
• It is first in-line to focus on legal protection for trade secrets in the cloud. A well-established similar concept is “information security”, which provides technical protection for trade secrets in the cloud e.g. encryption, hashing etc.
• In the domain of case law, despite of the jurisdiction constraint i.e. precedents (or court rulings) are binding on all courts within the same jurisdiction, this research is first in-line to use case law together with newly proposed Delphi Sampling method to provide legal protection for trade secrets in borderless online cloud environment.
• It is first in-line to implement notion of “confidentiality by design”, which focuses on a legal person or an enterprise. A well-established similar concept is “privacy by design” that focuses on a physical per-son or human being.
• By defying the myth that “smart contracts cannot be breached” and in the context of contract law, this research is first in-line to automate role of the court (evidential hearing).
In addition to the above mentioned research contribution in the domain of Law, following list briefly presents research contribution in the domain of ICT.
• In the context of multi-criteria decision analysis, this research is first in-line to identify and analyze noise in the data and solves related is-sue of structural uncertainty (or misspecification of criteria).
• In the context of machine learning, this research is first in-line to propose “self-regulated multi-criteria decision analysis” that operates without decision maker’s interference and hence, it can be used in the context where automation of decision making process is required.
• In the context of multidisciplinary research, this study is first in-line to propose a method of Delphi Sampling that seeks inter-disciplinary validation for research results.