# An Overview of Privacy Dimensions on the Industrial Internet of Things (IIoT)
## 6 Privacy Threats in the IIoT
Inventory assaults are the unlawful acquisition of information about the equipment's presence and attributes. Also, with the implementation of machine to machine vision [99; 100], intelligent devices can be questioned about their energy footprint, communication rates, reaction times, and other distinctive characteristics, which might be used to identify their kind and model, subject to limitations imposed by legal or presumably legal organizations. Thus, evil individuals who violate the privacy of an industry can assemble an inventory list of the gadgets in a particular building or factory, as well as information about how each device operates [17]. Here too, cryptography solutions have been proposed for aggregation mechanisms. This secure aggregation protocol meets the IoT requirements [101]. It evaluates its effectiveness in light of various system configurations, the wireless channel's impact on packet error rates, and private communication techniques [102]. 7. Linkage. This threat consists of connecting different previously separated systems so that combining the data and the sources reveals critical information that would be impossible to tell by individual plans. Moreover, to ensure the smooth operation of IIoT devices, it is essential to have flat networking that will allow them to function effectively. It is critical to have a high-quality open networking system for this purpose [103]. This particular factor in IIoT networks creates a security barrier. In this regard, industrial enterprises must thoroughly assess their security policies to ensure that IIoT devices are not vulnerable to threats [68]. Also, providers must understand the significance of adequately configuring the networking device and services and that data privacy entails various processes, such as efficiently removing sensitive information through data segregation [48]. Figure 5 depicts an emerging architecture that successfully predicts and assesses threat-related conditions in an industrial ecosystem while ensuring privacy and secrecy [104]. The above high-level depiction of the specific industrial privacy-preserving framework introduces an intelligent control mechanism to detect abnormalities in the Industry 4.0 communication network based on three main principles. The sensitive data is not transmitted through communication channels or stored in a central point of attack, and the learning algorithms are constantly updating their predictive power. However, a significant part of the responsibility lies with the hardware manufacturers. Often, the mechanisms and interoperability standards concerning the security of IIoT devices should be addressed or treated as a secondary consideration [105]. Usually, this is due to the requirement for a short period to implement an IoT device, simplify the design of its operating mechanisms, and reduce its overall cost. Therefore, those involved in IIoT delivery processes must consider privacy and develop privacy management interfaces built into the endpoint and web interface of the product or service [106]. This technology should enable the user industry to understand which privacy features are utilized by the ecosystem, what the Terms of Service are, and whether or not it is feasible to deactivate the disclosure of this information to the business' partners or rivals. This information management system will ensure that users have the right and capacity to regulate the information they disclose about themselves and their physical surroundings [107]. In light of the above-mentioned text, the IIoT presents unique privacy challenges and threats due to the large amounts of data generated, stored, and processed in industrial environments. Some of the most common privacy threats in the IIoT include Data Breaches, Cyberattacks, Insider Threats, Lack of Transparency and Unsecured Communications. To address these privacy threats, IIoT implementations must implement appropriate technical and organizational measures to protect sensitive information and personal data.