# Secure and Privacy-Respecting Documentation for Interactive Manufacturing and Quality Assurance
## 1 Introduction
In addition, individual reactions to people and functions that guide the worker step by step through the assembly process can be largely minimized if it is recognized that the assembly result is correct regardless of the individual procedure [18]. Without disturbing the worker in the execution of his activities, reached milestones can be proactively documented in the background with picture evidence, e.g., the bolting of safety-critical points, the quality-assuring inspection of welding spots or, in the simplest case, the correct insertion of the first-aid kit in the production of vehicles [19]. Considering the perceptual capabilities that a production environment gains through video-based acquisition modalities, a myriad of applications can be developed into truly smart production processes. However, video-based assistance and documentation systems also have clear downsides that have not been addressed sufficiently in the past. While video-based solutions offer a wide variety of different capture options with only one sensor, they are often criticized for capturing personal information in the sensor data, which leads to privacy and data security issues. Particularly with regards to widespread video-based surveillance systems, such as dashcams operated by ride-hailing companies, data privacy concerns regarding captured video footage have been a topic of public discourse for a while [20]. Recently, the Chinese ride-hailing enterprise Didi Global has been suspended on grounds of data security and privacy issues, further emphasizing the need for privacy-friendly data acquisition solutions [21]. While privacy-preserving dashcams have already been researched [22], to our knowledge there is no proposal for mitigating data privacy risks of video-based assistance systems in production environments. A recent survey, conducted among leaders in industry and academia, shows that both privacy protection and information security are considered to be prime challenges in the realization of smart manufacturing environments [5]. Hence, when advanced assistance and documentation systems acquire large amounts of data, video material in particular, it is crucial to embed the respective systems in the company processes in a manner that complies with data protection requirements and involves employees or employee representatives. It is particularly important to ensure that the data is only processed for legitimate purposes, such as simplifying work processes, while at the same time ensuring that technical and organizational measures are in place to prevent any misuse. The surreptitious monitoring of employees' work performance and access to video data without the consent of the recorded data subjects has to be prevented. In this paper, we describe a technical system architecture for a smart video documentation system (Section 2), for which we systematically derive data protection and data security requirements (Section 3). As our main contribution, in Section 4, we introduce an extended system architecture that includes advanced security mechanisms addressing these requirements and offering a high level of privacy protection for workers. We analyze the security of our approach and discuss its limitations in Section 5 before describing our proof-of-concept scenario and comparing our system with previous work in Section 6. Finally, we conclude with an outlook on possible solutions for more flexible and secure architectures in Section 7.