Lightning-fast and privacy-preserving outsourced computation in the cloud

Ximeng Liu,Yang Yang,Robert H Deng,Pengfei Wu

doi:10.1186/s42400-020-00057-3

Ximeng Liu, Yang Yang + Show 2 more

Open Access

https://doi.org/10.1186/s42400-020-00057-3

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Abstract

In this paper, we propose a framework for lightning-fast privacy-preserving outsourced computation framework in the cloud, which we refer to as LightCom. Using LightCom, a user can securely achieve the outsource data storage and fast, secure data processing in a single cloud server different from the existing multi-server outsourced computation model. Specifically, we first present a general secure computation framework for LightCom under the cloud server equipped with multiple Trusted Processing Units (TPUs), which face the side-channel attack. Under the LightCom, we design two specified fast processing toolkits, which allow the user to achieve the commonly-used secure integer computation and secure floating-point computation against the side-channel information leakage of TPUs, respectively. Furthermore, our LightCom can also guarantee access pattern protection during the data processing and achieve private user information retrieve after the computation. We prove that the proposed LightCom can successfully achieve the goal of single cloud outsourced data processing to avoid the extra computation server and trusted computation server, and demonstrate the utility and the efficiency of LightCom using simulations.

Highlights

THE internet of things (IoT), embedded with electronics, Internet connectivity, and other forms of hardware, is a computing concept that describes the idea of everyday physical objects being connected to the internet and being able to identify themselves to other devices
A quarter of the data will create in real-time, and 95% is to come from IoT real-time data
With the two properties given above, we show that our Paillier Cryptosystem Distributed Decryption (PCDD) have the polynomial homomorphism property, i.e., given [[ x1]], · · ·, [[ xn]] and a1, · · ·, an, it has

Summary

Introduction

THE internet of things (IoT), embedded with electronics, Internet connectivity, and other forms of hardware (such as sensors), is a computing concept that describes the idea of everyday physical objects being connected to the internet and being able to identify themselves to other devices. With large numbers of IoT devices, a colossal amount of data is generated for usage. According to IDC1, the connected IoT devices will reach 80 billion in 2025, and help to generate 180 trillion gigabytes of new data that year. A quarter of the data will create in real-time, and 95% is to come from IoT real-time data. With such a large volume, real-time data are generated; it is impossible for the resource-limited IoT devices to store and do the data analytics in time. The massive volume of data generated by IoT devices is outsourced to the cloud for long-term storage and achieve real-time online processing

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