Preserving Privacy in Distributed Computation via Self-Assembly

We present the tile style, an architectural style that allows the creation of distributed software systems for solving NP-complete problems on large public networks. The tile style preserves the privacy of the algorithm and data, tolerates faulty and malicious nodes, and scales well to leverage the size of the public network to accelerate the computation. We exploit the known property of NP-complete problems to transform important real-world problems, such as protein folding, image recognition, and resource allocation, into canonical problems, such as 3-SAT, that the tile style solves. We provide a full formal analysis of the tile style that indicates the style preserves data privacy as long as no adversary controls more than half of the public network. We also present an empirical evaluation showing that problems requiring privacy-preservation can be solved on a very large network using the tile style orders of magnitude faster than using existing alternatives.