A hybrid Improved Fully Homomorphic Encryption with AES to provide high security in Cloud Computing

Since this information may be accessible by a third party and could compromise the client's information's confidentiality, there is a barrier between the customer and the true location of his information. The most often used approach to bridging this security gap has been to first encrypt online data using traditional methods before sending it to the cloud service provider. But to decrypt the information and complete the calculations that are required, the customer must give the server a secret key. Using homomorphic encryption, mathematical calculations can be made on encrypted information without having to first decode it. The electrocardiogram (ECG) measures and finds arrhythmias in the circulatory system. It differ from individual to individual, these characteristics are now employed for identification. So it's crucial to secure an ECG signal. A safety method known as Homomorphic Encryption (HE) handles encrypted information without the need for decryption.The identical initial information findings are provided by HE. In this research, an Improved Fully Homomorphic Encryption (IFHE) technique using Advanced Encryption Standard (AES) is proposed for encoding the ECG measures to enhance safety while safeguarding the confidentiality of information while removing sharing key limitations. The information of the customer is encrypted in the cloud server discussed in this work, so required computations can be performed on the encrypted information. To do this, it is proposed that the method of assessment be added as a further layer of security to the AES technique, which then executes several homomorphic mathematical computations on the encrypted information in place of the initial information. To increase safety, a linear polynomial equation with changeable values is proposed for the assessment procedure.Additionally, the IFHEAES method has a 100% success rate in decryption (recovering the original signal) and 95.8% efficiency in categorization. Its decryption and encryption reaction times are almost 6 times and 3 times faster than those of other techniques, correspondingly. This is so that it can effectively deal with the noise those results from any FHE technique because it is proposed to be built on computationally light matrix computations. As a result, IFHEAES offers the best privacy and security when processing and resistant to threats.