Abstract Garbled circuits are a fundamental cryptographic primitive that allows two or more parties to securely evaluate an arbitrary Boolean circuit without revealing any information beyond the output using a constant number of communication rounds. Garbled circuits have been introduced by Yao (FOCS’86) and generalized to the multi-party setting by Beaver, Micali and Rogaway (STOC’90). Since then, several works have improved their efficiency by providing different garbling schemes and several implementations exist. Starting with the seminal Fairplay compiler (USENIX Security’04), several implementation frameworks decoupled the task of compiling the function to be evaluated into a Boolean circuit from the engine that securely evaluates that circuit, e.g., using a secure two-party computation protocol based on garbled circuits. In this paper, we show that this decoupling of circuit generation and evaluation allows a subtle attack on several prominent garbling schemes. It occurs when violating the implicit assumption on the circuit that gates have different input wires which is most often not explicitly specified in the respective papers. The affected garbling schemes use separate calls to a deterministic encryption function for the left and right input wire of a gate to derive pseudo-random encryption pads that are XORed together. When a circuit contains a gate where the left and right input wire are the same, these two per-wire encryption pads cancel out and we demonstrate that this can result in a complete break of privacy. We show how the vulnerable garbling schemes can be fixed easily.

Fingerprinting is a commonly used technique to provide accurate localization for indoor areas, where global navigation satellite systems, such as GPS and Galileo, cannot function or are not precise enough. Although fingerprint-based indoor localization has gained wide popularity, existing solutions that preserve privacy either rely on non-colluding servers or have high communication which hinder deployment. In this work we present FAPRIL, a privacy-preserving indoor localization scheme, which takes advantage of the latest secure two-party computation protocol improvements. We can split our scheme into two parts: an input independent setup phase and an online phase. We concentrate on optimizing the online phase for mobile clients who run on a mobile data plan and observe that recurring operands allow to optimize the total communication overhead even further. Our observation can be generalized, e.g., to improve multiplication of Arithmetic secret shared matrices. We implement FAPRIL on mobile devices and our benchmarks over a simulated LTE network show that the online phase of a private localization takes under 0.15 seconds with less than 0.20 megabytes of communication even for large buildings. The setup phase, which can be pre-computed, depends heavily on the setting but stays in the range 0.28 - 4.14 seconds and 0.69 - 16.00 megabytes per localization query. The round complexity of FAPRIL is constant for both phases.

We present a privacy-preserving indoor localization scheme based on received signal strength measurements, e.g., from WiFi access points. Our scheme preserves the privacy of both the client's location and the service provider's database by using secure two-party computation instantiated with known cryptographic primitives, namely, Paillier encryption and garbled circuits. We describe a number of optimizations that reduce the computation and communication overheads of the scheme and provide theoretical evaluations of these overheads. We also demonstrate the feasibility of the scheme by developing a proof-of-concept implementation for Android smartphones and commodity servers. This implementation allows us to validate the practical performance of our scheme and to show that it is feasible for practical use in certain types of indoor localization applications.