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Organizations nowadays are storing and performing computation of the data on the cloud instead of handling themselves. Cloud Service Providers (CSPs) provide these services at an affordable cost and low maintenance. But to ensure compliance and retain privacy, organizations need to transfer the data in an encrypted format, which does ensure the confidentiality of the data. However, once the data reaches the cloud, the CSP has to decrypt the data to perform operation or computation.
What is Homomorphic Encryption?
Why do we need Homomorphic Encryption?
Types of Homomorphic Encryption
- Partial Homomorphic Encryption (PHE) (supports either addition/multiplication, but not both)
- Fully Homomorphic Encryption (FHE) (supports both addition and multiplication)
- Private Search
Search Engines rely on ads to generate revenue. While serving searches to their users, search engines get a better view of the user’s preferences. This does help them provide customized ads for the user they serve. Homomorphic encryption does solve the problem. Search Engines can crawl the encrypted data, serve them as the algorithm is designed to, and serve the user with encrypted data. The user would get the desired result, while the search engines remain unaware of the data requested, which keeps preferences private and more challenging to serve ads.
- Encrypted Databases
In any cyber-attacks, databases are often the most crucial infrastructure to protect. It may cost an organization a considerable fine in compliance and have a bad reputation to go along. Several security measures are kept in place, which includes Encrypting a database. In case of a breach, the database would remain encrypted and decrypted by a specific key, preventing unauthorized access to the database.
If we employ the standard encryption, the encrypted database will not allow any operations on the records. We can use deterministic encryption, order-preserving encryption, and order-revealing encryption to support the encrypted database. But these would lead to leakages, such as memory access patterns and search patterns.
With Homomorphic Encryption, it is possible to encrypt data in the database to obtain confidentiality, while we can also perform operations and computation on the data. Only authorized users with the key to decrypt the database can access the data in the database.
- Computation on Cloud
Cloud Computing saves money and reduces maintenance that an organization needs to maintain its infrastructure for the services offered. Organizations can lease cloud infrastructure on a need basis to run their applications. CSPs also provides the ability to scale up according to the load on the infrastructure. Since the service providers typically manage clouds, organizations require the CSP to be compliant and get better privacy and security for their organization.
If we choose to keep the data encrypted on the cloud and perform operations on those encrypted data, it will make CSP’s compliance and security measures less relevant. CSPs can maintain the infrastructure that store and process the encrypted data, while never accessing the plaintext.
Limitations and Drawbacks
Homomorphic Encryption in the current state is computationally expensive and practically inefficient. It can certainly be used to encrypt data, while we can perform different computations on the data. HE enables privacy-preserving computation, which helps us work with untrusted environments while maintaining the data’s confidentiality. Check out Format Preserving Encryption if interested in privacy-preserving computations.