Technology Innovations Model of Artificial Intelligence to Stop Industrial Espionage in Manufacturing Establishments

Abstract

In the digital age and at smart manufacturing sites, the production units have been facing a lot of challenges concerning industrial espionage and are vulnerable, critical, and under a growing threat that needs cybersecurity practices, policies, and cryptography in place. Most manufacturing firms have been facing the biggest challenge, as they have been facing critical issues concerning security, confidentiality, availability, and accessibility of the confidential manufacturing process, formulas, and core research and development credentials. In the United States, there have been a high number of cybersecurity data breach and industrial espionage cases reported, with manufacturing and other industries being the most heavily affected; of the 1579 data breach cases reported, 620 were related to manufacturing. Most industrial sites must protect their intellectual property and maintain confidentiality while also securing operational and manufacturing transactions across multiple sites. Key critical data, day-to-day operational master data, corporate key data, and data governances, as well as formulas, key production compositions, and valuable intellectual property (IP), are stored in secure locations and accessible to authorized users in the organization. However, there have been a few cases of data theft by hackers and other people who shouldn't have access to it on real-world systems, as this could happen due to access to virtual reality. This could include potential risks and critical losses to industrial manufacturing segments that must bear the loss of business due to an inability to meet global trade compliance requirements, as well as data losses at the enterprise level. In operational planning, industrial espionage is one of the most critical cases that could potentially harm the reputation of individual manufacturing sectors and render them unable to fulfill customer orders (MTS or MTO). Several major cases of industrial espionage and trade secret theft have been reported and published in academic journals. In 2012, the NSA director and commander of US Cyber Command reported that industrial espionage and cyber espionage exclusive to industrial manufacturing sites could result in a loss of $ 338 billion per year, which is a significant amount of money and data. Some technology innovations models (AI, ML, and quantum computing, ERP-SAP, and Zero-trust) AI, ML, or quantum cyber security models could potentially save data and prevent IP and other credentials from being stolen, as well as update the robust security and cybersecurity platform to protect against potential industrial espionage or future threats within the manufacturing sites. Most industrial manufacturing sites, such as defense production, airship production, pharmaceuticals, or even a high-tech manufacturing company where technologies and innovations are crucial to performance, see intellectual property (IP) as the most important and valuable thing that needs to be secured and protected. Only authorized employees or vendors should be able to access IP, and an audit and log trial should be kept. Per KPMG research studies, industrial espionage could be easily targeted concerning accessing back-office systems, like ERP, production control systems, manufacturing execution, and inventory databases, to steal the critical product formulas and credentials to manage to copy the most sensitive trade secrets, which could be potential IE.