Blockchain-Based Digital Rights Management Techniques

Introduction

Organizations started focusing on data driven Artificial Intelligence (AI) designing systems by aiming a sophisticated and collaborative development of applications [Darabant and Darabant], [Walsh]. The collaboration process in AI helps to build the engineering processes by reusable AI objects and specialization systems such as deep learning methods and data set models. The reusable objects have been developed or gathered by including a third party process for designing the final system or application. The potential advantages of using these processes are the reduced time and development process and components access that enable several engineering processes for higher AI performance. In addition, the interesting features are supported by the expansion of AI pipelines [Song], and data revelation tools such as Orange [Xiao], open source machine learning techniques and the materialize of several data marketplaces [Knapp], [Singhal].

Further, the collaborative schemes, however, comes at a price. It inflicts at least three primary challenges on the designing process. Initially, the intrinsic usage of data hoists various privacy anxieties. These threats become even higher regarding the trait of datasets being communal. After that, Data-driven artificial intelligence techniques aim at recognizing the unidentified relationships within the data. Though, when using typical security enforcing techniques such anonymous schemes or restriction in information collection, then it can’t be barred that intrinsic relationships inside the data sets are not deleted or captured. Therefore, as a result, these data sets are fetching of no worth. Whilst such typical concepts are of high cost for specific purposes might bang the AI objects usability in general. Therefore, a quandary for the general notion of alliance based on reusability occurs. Then, the reuse of objects in collaborative schemes necessitates trust amongst the users and developers. This trust assortments from comply with licenses among developers to authorizing supremacy on objects as requisite by individuals and societies, e.g. GDPR-like and enabling GDPR concepts on the usage of information and objects in Europe. Therefore, this chapter goal is to address these primary challenges by providing the insight to the security and privacy necessities in collaborative development. In addition, it will offer an initial classification of privacy and Digital Rights Management (DRM) and the attacks against AI objects in the pipeline. Further, the chapter discusses the need of transparency while sharing the data or ensuring the privacy among various individuals. Furthermore, the usage of Blockchain technology in digital marketing for AI objects collaboration processes. Finally, the chapter highlighted the GDPR act and its potential insinuation for Bonseyes such as AI marketplaces and illustrates potential behavior of disobey the DRM connected with the artefacts. It further delineated a Blockchain security architecture to avoid the attacks.

In today’s world, network system and cloud computing organizations are crucial factors in the development and operation of IoT applications. 2017, in according to the appraisal of the Asian Cloud Computing Association ACCA also known as cloud asia and, resource provision, a significant service in Cloud Computing, is flattering a major insist in scientific request. Most of the traditional cloud computing structures in Vietnam have been ensuring services with various challenges and issues as listed below:

• i.

  The price of translation involves services offered through remote information centers and is construct on practical servers borrowed from overseas, so the price is very costly.

• ii.

  The ease of use of human income to provide the action of the entire structure is unsecured and insufficient.

• iii.

  Cloud computing capital often emerge as the only admission point for all computing servers, so there is no assurance for consumer about reliable time and design .

• iv.

  Cloud centers have not build service stipulation systems that must have superior characterstics of suppleness in security recovery, scalability and system congestion.