Excerpt:
"Homomorphic encryption is similar in that it lets data processors manipulate selected ‘raw materials’ such as sales figures or medical data, but keeps the plain-text data private. That is because the data doesn’t have to be decrypted to be used. Only the end result of the computation is presented in plain text. Because homomorphic encryption is mathematically and computationally very challenging, it was an intriguing theoretical discussion long before it became a practical option. And it is still in development.
'There are no theoretical limits to the computations that can be carried out using homomorphic encryption,' says Ellison Anne Williams, CEO and founder of Enveil, a company that specialises in privacy enhancing technologies. 'But there are practical constraints.' In particular, homomorphic encryption is still limited in terms of the functions it can carry out and it needs a lot of processing power to run."
Read the full Raconteur article here.
