[Resource Topic] 2020/1181: TinyGarble2: Smart, Efficient, and Scalable Yao’s Garble Circuit

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TinyGarble2: Smart, Efficient, and Scalable Yao’s Garble Circuit

Authors: Siam Hussain, Baiyu Li, Farinaz Koushanfar, Rosario Cammarota


We present TinyGarble2 – a C++ framework for privacy-preserving computation through the Yao’s Garbled Circuit (GC) protocol in both the honest-but-curious and the malicious security models. TinyGarble2 provides a rich library with arithmetic and logic building blocks for developing GC-based secure applications. The framework offers abstractions among three layers: the C++ program, the GC back-end and the Boolean logic representation of the function being computed. TinyGarble2 thus allowing the most optimized versions of all pertinent components. These abstractions, coupled with secure share transfer among the functions make TinyGarble2 the fastest and most memory-efficient GC framework. In addition, the framework provides a library for Convolutional Neural Networks (CNN). Our evaluations show that TinyGarble2 is the fastest among the current end-to-end GC frameworks while also being scalable in terms of memory footprint. Moreover, it performs 18× faster on the CNN LeNet-5 compared to the existing scalable frameworks.

ePrint: https://eprint.iacr.org/2020/1181

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