Homomorphic Encryption is an interesting application of data encryption in that it allows us to encrypt data in a way such that we can perform computations on it without first having to decrypt it. The more formal definition states “Homomorphic encryption is the conversion of data into ciphertext that can be analyzed and worked with as if it were still in its original form. Homomorphic encryption enables complex mathematical operations to be performed on encrypted data without compromising the encryption.”
I have been following the work on Homomorphic Encryption solutions since 2017 onwards, which was when I first became aware of it and have read tons of articles and papers on it. The overview by Jeremy Kun is probably the best one I have seen so far. His post with A High-Level Technical Overview of Fully Homomorphic Encryption goes into enough technical details that you understand it without going so deep that you are lost in the details.
Homomorphic encryption lets you encrypt data in such a way that you can run programs on it without ever decrypting it. This means that the computer running the program has no access to the underlying data while running the program—neither via intermediate computed values, nor even the result. In particular, if a nefarious human had access to the machine’s raw memory, they still could not learn any information about the underlying data (without breaking the cryptography). A user sends the program an encrypted input, and when the program is done, the encrypted result is sent back to the user to decrypt.
Running a program on encrypted data sounds magical. It works by choosing an encryption scheme that is “compatible” with addition and multiplication in the following sense:
Adding ciphertexts gives you an encryption of the sum of the underlying plaintexts.
Multiplying two ciphertexts give you an encryption of the product of the underlying plaintexts.Given this power, you can encrypt your data bit by bit, express your program as a boolean circuit—an XOR gate is addition and an AND gate is multiplication—and simulate the circuit. Since XOR and AND form a universal basis for boolean logic, you can always decompose a circuit this way.
Check it out if you are curious about Homomorphic Encryption and want to learn more.
– Suramya