Encryption within process control is a well-established phenomenon that provides data security during various operational procedures. While more common encryption types primarily ensure data safety during transmission, homomorphic encryption provides protection within the evaluation phase, preserving data privacy. Despite the strong privacy protection, security vulnerabilities are still present in cloud-based environments. A critical yet often overlooked issue is the potential for ciphertext modifications, which can be caused by various factors. These modifications can be the result of unauthorized alterations performed by the cloud service provider, external adversarial attacks, or unintended errors introduced during data processing and evaluation. Such manipulations pose a significant risk to the integrity and safe operation of systems that utilize outsourced control evaluation. To the best of our knowledge, these threats have not been addressed within the context of homomorphically encrypted process control setups. In our research, we aim to analyze these security challenges by identifying potential vulnerabilities and propose an algorithm for the CKKS cryptosystem, as it is the most commonly used in process control applications, that can detect unauthorized alterations to encrypted data. Our approach enhances the safety of encrypted process control systems, ensuring that computation results remain trustworthy despite potential threats in the cloud environment. We demonstrate the effectiveness of our method in safeguarding homomorphic encryption applications from unauthorized ciphertext manipulation using punctual analysis and experimental validation. The authors gratefully acknowledge the contribution of the Scientific Grant Agency of the Slovak Republic under the grant 1/0263/25. This paper is also funded by the European Union’s Horizon Europe under grant no. 101079342 Fostering Opportunities Towards Slovak Excellence in Advanced Control for Smart Industries and no. 09I01-03-V04-00024 Slovak Research Excellence in Advanced Control for Smart Industries.