Holistic Security and Safety for Factories of the Future

Abstract

The accelerating transition of traditional industrial processes towards fully automated and intelligent manufacturing is being witnessed in almost all segments. This major adoption of enhanced technology and digitization processes has been originally embraced by the Factories of the Future and Industry 4.0 initiatives. The overall aim is to create smarter, more sustainable, and more resilient future-oriented factories. Unsurprisingly, introducing new production paradigms based on technologies such as machine learning (ML), the Internet of Things (IoT), and robotics does not come at no cost as each newly incorporated technique poses various safety and security challenges. Similarly, the integration required between these techniques to establish a unified and fully interconnected environment contributes to additional threats and risks in the Factories of the Future. Accumulating and analyzing seemingly unrelated activities, occurring simultaneously in different parts of the factory, is essential to establish cyber situational awareness of the investigated environment. Our work contributes to these efforts, in essence by envisioning and implementing the SMS-DT, an integrated platform to simulate and monitor industrial conditions in a digital twin-based architecture. SMS-DT is represented in a three-tier architecture comprising the involved data and control flows: edge, platform, and enterprise tiers. The goal of our platform is to capture, analyze, and correlate a wide range of events being tracked by sensors and systems in various domains of the factory. For this aim, multiple components have been developed on the basis of artificial intelligence to simulate dominant aspects in industries, including network analysis, energy optimization, and worker behavior. A data lake was also used to store collected information, and a set of intelligent services was delivered on the basis of innovative analysis and learning approaches. Finally, the platform was tested in a textile industry environment and integrated with its ERP system. Two misuse cases were simulated to track the factory machines, systems, and people and to assess the role of SMS-DT correlation mechanisms in preventing intentional and unintentional actions. The results of these misuse case simulations showed how the SMS-DT platform can intervene in two domains in the first scenario and three in the second one, resulting in correlating the alerts and reporting them to security operators in the multi-domain intelligent correlation dashboard.

Adoption of Cybersecurity in the Chilean Manufacturing Sector: A First Analytical Proposal

“…A second group accounts for cybersecurity and the development of some specific technologies, e. g. IoT, 3D printing, Blockchain, Digital Twin, among others. [13], [14], [15], [16], [17], [18] b) Regarding the results: A first group proposed different methodologies or tools to detect anomalies and attacks [13], [14], [15], [18]. Meanwhile, we have a second group that identified barriers or risks in implementing Industry 4.0 enabling technologies, among which is cybersecurity.…”

“…[11], [12], [16]. On the other hand, there are works oriented to explore a set of techniques or tools through simulation or cases [13], [14], [14], [14], [18]. In this sense, the works that use sustainability reports [10], surveys of organizations [19], and literature review plus cases to generate a diagnosis [17] stand out.…”

Empirical Study of Fully Homomorphic Encryption Using Microsoft SEAL

“…In today's digital age, the exponential growth of data generated by the Internet of Things (IoT) and other digital platforms has led to the emergence of vast repositories of information known as data lakes [1,2]. These expansive, fluid collections of raw data, stored in their native format, offer unprecedented opportunities for analytics, innovation, and personalized services.…”