Flexibility and mobility of modern value chains have created a need for continuous information exchange between involved chain parties. In such process industries, many companies share their manufacturing assets with each other and thereby allow partners to have control over them. In this way, some sensitive essential information about operations and control methods could be leaked from the asset supplier to the user and vice versa. Therefore, such information sharing raises confidentiality concerns between the service provider and its operator. The goal of this work is to apply and evaluate a confidentiality-preserving information sharing model for a time series use case in process industries. There are various ways to maintain privacy of the sensitive information, such as anonymization and encryption. To preserve control for the user and to allow data gathering by the vendor about asset operation, homomorphic encryption methods could be implemented. Homomorphic encryption allows for the preservation of confidentiality of the data while enabling computations on the encrypted data. The main focus of this study is an investigation of homomorphic encryption schemes with multiplicative properties, such as RSA and ElGamal, which can be applied to process data within information exchanges. This research investigates the probabilistic and the deterministic homomorphic algorithms with respective differences in encryption and decryption speeds. This approach is based on the simulation of the use case between asset vendor and asset operator. The confidentiality model of the information exchange sustains the zero-knowledge proof between involved value chain partners. The result implies the adaptability of both methods within the privacy-preserving sharing model. This study is limited to a use case with the application of partial homomorphic cryptosystems in process industries. The outcome highlights the statistical justification of the application of multiplicative homomorphic encryption (MHE) for confidentiality preservation.