Homomorphic encryption is a type of encryption method that allows computations to be performed on encrypted data without first decrypting it with a secret key. The results of the computations also remain encrypted and can only be decrypted by the owner of the private key. Homomorphic encryption can be used for privacy-preserving outsourced storage and computation. This means that data can be encrypted and sent to a cloud service provider (CSP) for processing, without revealing any information to the CSP or anyone else who might intercept the data. Homomorphic encryption can enable new services and applications that require processing confidential data on a large number of resources, such as machine learning, data analytics, health care, finance, and voting.
A) Processing data on a server after decrypting in order to prevent unauthorized access in transit is not a common use case for homomorphic encryption, because it does not take advantage of the main feature of homomorphic encryption, which is computing over encrypted data. This use case can be achieved by using any standard encryption method that provides confidentiality for data in transit.
B) Maintaining the confidentiality of data both at rest and in transit to and from a CSP for processing is not a common use case for homomorphic encryption, because it does not take advantage of the main feature of homomorphic encryption, which is computing over encrypted data. This use case can be achieved by using any standard encryption method that provides confidentiality for data at rest and in transit.
D) Storing proprietary data across multiple nodes in a private cloud to prevent access by unauthenticated users is not a common use case for homomorphic encryption, because it does not involve any computation over encrypted data. This use case can be achieved by using any standard encryption method that provides confidentiality for data at rest.
https://www.splunk.com/en_us/blog/learn/homomorphic-encryption.html
https://research.aimultiple.com/homomorphic-encryption/