A DevSecOps-based Assurance Process for Big Data Analytics

Abstract

Today big data pipelines are increasingly adopted by service applications representing a key enabler for enterprises to compete in the global market. However, the management of non-functional aspects of the big data pipeline (e.g., security, privacy) is still in its infancy. As a consequence, while functionally appealing, the big data pipeline does not provide a transparent environment, impairing the users' ability to evaluate its behavior. In this paper, we propose a security assurance methodology for big data pipelines grounded on the DevSecOps development paradigm to increase trustworthiness allowing reliable security and privacy by design. Our methodology models and annotates big data pipelines with non-functional requirements verified by assurance checks ensuring requirements to hold along with the pipeline lifecycle. The performance and quality of our methodology are evaluated in a real walkthrough analytics scenario.

An assurance process for Big Data trustworthiness

“…This paper is in line with our previous work [11], where we first try to address the above gaps but in the framework of DevOps processes applied to Big Data pipelines. In this paper, we depart from the development process adopted, and from the best of our knowledge we present the first attempt to address the general problem of Big Data pipeline assurance.…”

Optimizing extreme manufacturing framework: a secure and efficient 3D printing integration framework

“…The iterative refinement process incorporated feedback from experts, refining accuracy and clarity. The integration of pivotal concepts, such as Digital Thread Integration and Cybersecurity Emphasis, remained central [1][2][3][4][5][6]. While visual content creation was suggested using appropriate tools, the synthesis of concise framework descriptions aimed to offer a comprehensive understanding of each architecture's structural and operational dynamics [9,15].…”

“…In the ever-evolving landscape of manufacturing, the integration of extended manufacturing frameworks with advanced 3D printing technologies represents a pivotal advancement. This study introduces a comprehensive framework that not only streamlines traditional manufacturing processes but also catalyzes innovation and efficiency [1,2]. The Digital Thread Integration lays the groundwork for real-time collaboration and data continuity throughout the product lifecycle [3,4].…”