| Abstrakt: |
With the increasing prevalence of Internet-of-Things (IoT), there is a growing demand for high-performance equipment that ensures data integrity and privacy-enabled security in various image generation applications. This paper presents a novel image encryption approach that utilizes a combination of optimization and encryption techniques designed specifically for the IoT domain. Homomorphic Encryption allows for the processing of encrypted data without the need for decryption, ensuring that unauthorized individuals are unable to access the plaintext information. This feature is exceptional in the realm of secure computations. When the hybrid optimization techniques are combined, they work together to significantly enhance the efficiency of data encryption. The IoT has brought about significant changes in various fields such as healthcare, smart home, and office automation, by establishing interconnected networks. However, the image data communicated through IoT networks is self-explanatory in this aspect, high sensitivity and mobility certainly makes it necessary to highlight on robust encryption for protection against illegal access or breaches. While traditional encryption methods work reasonably well for most purposes, they are not practical in a large number of IoT contexts because the smart devices required to perform them cannot be powerful generally and also need real time performance. The technology called Homomorphic Encryption has come out as the most functional answer here that helps in solving this problem of processing data while keeping it encrypted and without any intermediary steps (which may be a cause for enabling leakages). It is of utmost importance to prioritize this, particularly for IoT devices that regularly handle personal and sensitive information. One can probably say that homomorphic encryption has some good positive sides, but it is also computationally heavy and might not be apt for small resource-constrained IoT devices. Furthermore, there is scope of improving how to carry these scales over multiple dimensions and thinking about cost in terms of performance trade-off or security investing or resource spending etc. An effective strategy involving the combination of optimization algorithms can enhance performance and enable the practical use of Homomorphic encryption in IoT applications. The study validated this method by their experiments on largescale IoT devices including all sizes of compute capability. This was a good indication that the speed of encryption operations and resource allocation had greatly benefited from this, thereby enhancing security. This Hybrid Optimization methodology turns out to be useful not only by reducing the computation load due to homomorphic encryption but also extends this practically implementable on real-time conditions for IoT applications. Our trial results clearly demonstrated that our hybrid optimization-enhanced homomorphic encryption is more efficient and secure than standard encryption methods. The technology was able to get near real-time usage without violating integrity and data privacy. [ABSTRACT FROM AUTHOR] |
