In this paper, we introduce the Fully Homomorphic Integrity Model (HIM), a novel approach designed to enhance security, efficiency, and reliability in encrypted data processing, primarily within the health care industry. HIM addresses the key challenges that noise accumulation, computational overheads, and data integrity pose during homomorphic operations. Our contribution of HIM: advances in noise management through the rational number adjustment; key generation based on personalized prime numbers; and time complexity analysis details for key operations. In HIM, some additional mechanisms were introduced, including robust mechanisms of decryption. Indeed, the decryption mechanism ensures that the data recovered upon doing complex homomorphic computation will be valid and reliable. The healthcare id model is tested, and it supports real-time processing of data with privacy maintained concerning patients. It supports analytics and decision-making processes without any compromise on the integrity of information concerning patients. Output HIM promotes the efficiency of encryption to a greater extent as it reduces the encryption time up to 35ms and decryption time up to 140ms, which is better when compared to other models in the existence. Ciphertext size also becomes the smallest one, which is 4KB. Our experiments confirm that HIM is indeed a very efficient and secure privacy-preserving solution for healthcare applications

翻译：本文提出全同态完整性模型（HIM），这是一种旨在提升加密数据处理安全性、效率与可靠性的创新方法，主要面向医疗健康领域。HIM解决了同态运算过程中噪声累积、计算开销和数据完整性等关键挑战。本研究的核心贡献在于：通过有理数调整实现噪声管理机制的突破；基于个性化素数的密钥生成方案；以及对关键操作时间复杂度的详细分析。HIM引入了多项增强机制，包括鲁棒的解密机制。该解密机制确保经过复杂同态计算后恢复的数据具备有效性与可靠性。经测试，该医疗领域模型支持在保护患者隐私前提下的实时数据处理，可在不损害患者信息完整性的条件下支持分析决策流程。HIM显著提升了加密效率，其加密时间缩短至35毫秒，解密时间降至140毫秒，优于现有同类模型。密文尺寸亦缩减至最小4KB。实验证实，HIM确实是为医疗应用提供的高效安全隐私保护解决方案。