Download Engineering Secure Two-Party Computation Protocols: Design, by Thomas Schneider PDF

By Thomas Schneider

Secure two-party computation, referred to as safe functionality overview (SFE), allows jointly mistrusting events, the buyer and server, to guage an arbitrary functionality on their respective inner most inputs whereas revealing not anything however the outcome. initially the approach was once thought of to be too inefficient for functional privacy-preserving purposes, yet in recent times swift speed-up in pcs and conversation networks, algorithmic advancements, computerized iteration, and optimizations have enabled their software in lots of scenarios.

The writer deals an in depth evaluate of the main sensible and effective glossy innovations utilized in the layout and implementation of safe computation and similar protocols. After an advent that units safe computation in its greater context of different privacy-enhancing applied sciences reminiscent of safe channels and depended on computing, he covers the fundamentals of essentially effective safe functionality review, circuit optimizations and structures, hardware-assisted garbled circuit protocols, and the modular layout of effective SFE protocols.

The objective of the author's study is to exploit set of rules engineering ways to engineer effective safe protocols, either as a wide-spread device and for fixing sensible purposes, and he achieves a superb stability among the idea and applicability. The booklet is vital for researchers, scholars and practitioners within the sector of utilized cryptography and data safety who target to build useful cryptographic protocols for privacy-preserving real-world applications.

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See Also. Parts of the following results are based on [144, Sect. 5]. , their amount of money) without revealing more information than the outcome of the comparison to the other party. More concretely, client C holds a private -bit value x and server S holds a private -bit value y. The output bit z = [x < y] should be revealed to both. In the semi-honest case it is sufficient to consider the case where C obtains the output and forwards it to S. An example application that can be reduced to multiple invocations of secure comparison is the secure computation of the kth-ranked element of the union of two datasets held by two parties [1].

Notation 2 (Costs of boolean gates and circuits) We denote the costs of (non-trivial) d-input gates with |Gd |. Similarly, the costs of a boolean circuit C, denoted as |C|, are the sum of the costs of its gates. Example 3 In the point-and-permute GC construction [157] the garbled table of a non-trivial d-input gate has size |Gd | = 2d · (t + 1) bits (cf. Sect. 2). , non-trivial d-input gates have at most the same cost as non-trivial (d + 1)-input gates: |Gd | ≤ |Gd+1 |. This assumption is fulfilled for the computation and communication costs of all GC constructions presented in Sect.

1, using an efficient GC-based SFE protocol with free XORs, is more efficient than previous comparison protocols. 1 Comparison with Pre-Computations In many practical application scenarios it is beneficial to shift as much of the computation and communication cost of a protocol into an interactive setup (pre-computation) phase, which is executed before the parties’ inputs are known, while the parties’ workload is low. In contrast to many protocols based on HE, almost the entire cost of GC-based protocols can be shifted into the setup phase.

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