Edge computing has the potential to enable new forms of privacy-preserving computation, such as secure multi-party computation and homomorphic encryption, by moving data processing and computation closer to where the data is generated and consumed.
Secure multi-party computation (SMPC) is a cryptographic technique that allows multiple parties to compute on their data without revealing their private information to each other. Instead of sharing their data with one another, parties use cryptographic protocols to jointly perform computation while keeping their data secret. By distributing computation tasks to multiple parties, SMPC makes it possible to perform data analysis without ever revealing any of the data to a central authority. Edge computing can facilitate SMPC by allowing the computation to be performed locally on devices within the network, without the need to send data to a centralized server for processing. The ability to perform computation locally enables parties to maintain control of their data while still benefiting from collaborative data analysis.
Homomorphic encryption is a technique that allows computations to be carried out on encrypted data, without decrypting it first. This means that sensitive data can remain encrypted at all times, even during computation, reducing the risk of data breaches or leaks. Edge computing can enable homomorphic encryption by allowing data to be processed locally on devices at the edge of the network. By processing data on the edge, the need to transmit sensitive data to a central server for processing is reduced, reducing the risk of data breaches or leaks that could occur during transmission.
For example, imagine a smart city where multiple sensors are collecting data on the environment, traffic, and public health. With edge computing, it would be possible to perform SMPC on this data, allowing different agencies like the police, health agencies, and universities to collaboratively analyze the data without compromising privacy. Similarly, homomorphic encryption could be used to analyze data from these sensors without ever revealing the data to any of the parties involved, enabling sophisticated data analysis while maintaining privacy.
In summary, edge computing has the potential to enable new forms of privacy-preserving computation, such as SMPC and homomorphic encryption, by allowing computation to be performed locally on devices at the edge of the network. This can help to maintain privacy, while still allowing for collaborative data analysis.