An improved method for privacy-preserving web-based data collection - PowerPoint PPT Presentation

An improved method for privacy-preserving web-based data collection Riivo Talviste Supervisor: Dan Bogdanov, MSc April 24, 2009

Outline of the Talk ● State of the Art ● Problem statement ● Improved architecture ● Implementation ● Demo

The Danisco Auction (1) ● In Denmark farmers grow sugar beets, which they sell to the Danisco company. ● EU reduced support, so they conducted a nation-wide double auction. ● A survey showed that farmers really care about their confidentiality.

Survey Results It is important that my bids are kept confidential Agree strongly 35% Agree 43% Don't know 18% Disagree 2% Disagree strongly 1% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

The Danisco Auction (2) ● Auctioneer = {Danisco, DKS, SIMAP project} ● The first large-scale practival application of multiparty computation (MPC). ● Held in two phases: – Placing and gathering bids, – Processing bids and calculating market clearing price (MCP).

The Danisco Auction Architecture Phase 1 Phase 2 Danisco session Web server Danisco website database MPC Java applet public keys login DKS SIMAP encrypted shares Farmer's computer

Problem Statement ● Farmer has to trust the web server unconditionally, as it can send wrong public keys. ● Java applet is a fat-client application, not everybody has Java Runtime Environment (JRE) installed.

Our Solution ● Similar to the Danisco auction architecture. ● Built on the Sharemind framework.

Our Architecture Web server Miner 1 Miner 1 web server MPC Flex application share Miner 2 web server Miner 2 Miner 3 share client's share computer Miner 3 web server HTTPS connection

Security Analysis Confidentiality is satisfied by: ● Secret sharing ● Public Key Infrastructure (PKI) and direct HTTPS connections. – Client does not have to trust anybody unconditionally – Potential security risk : malicious miners with certificates already trusted by client are still a threat.

Implementation ● Adobe Flex technology – Free, open source framework, – MXML, a XML-based language for layout, – ActionScript 3, an object-oriented language for client logic, – Thin-client, – Run by Adobe Flash Player. ● Recent survey shows that 99.0% of Internet- enabled desktops have Flash Player.

Conclusion ● First large-scale practical MPC applications are already in use. ● We proposed an architecture with stronger confidentiality guarantees than the ones currently in use. ● We implemented it using Adobe Flex, the most spread web-based software platform.

Questions!? Thank You!

An improved method for privacy-preserving web-based data collection - PowerPoint PPT Presentation

An improved method for privacy-preserving web-based data collection Riivo Talviste Supervisor: Dan Bogdanov, MSc April 24, 2009 Outline of the Talk State of the Art Problem statement Improved architecture Implementation

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An improved method for privacy-preserving web-based data collection - PowerPoint PPT Presentation

An improved method for privacy-preserving web-based data collection Riivo Talviste Supervisor: Dan Bogdanov, MSc April 24, 2009 Outline of the Talk State of the Art Problem statement Improved architecture Implementation

Preserving the Privacy of Sensitive Relationships in Graph Data Motivation Valuable Data! No

Privacy preserving data mining randomized response and association rule hiding Li Xiong

Privacy-Preserving Query Processing over Encrypted Data in Cloud CS573 Data Privacy and Security

DIMACS/PORTIA Workshop on Privacy Preserving Data Mining Data Mining &amp; Information Privacy:

Collaborative Privacy Preserving Data Mining in Vertically Partitioned Databases Ehud Gudes

Network Privacy Mostly issues of preserving privacy of data flowing through network Start

Secure Multiparty Computation Introduction to Privacy Preserving Distributed Data Mining Li

On k -anonymity and the curse of dimensionality Introduction An important method for privacy

New Directions in Privacy- preserving Machine Learning Kamalika Chaudhuri University of

Privacy preserving data mining multiplicative perturbation techniques Li Xiong CS573 Data

Motivation Dramatic increase in digital data Privacy-Preserving Data Mining World Wide

Helper data schemes for privacy-preserving biometrics Boris kori TU Eindhoven van der

On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis James Foulds,* Joseph

Privacy Preserving Protocols Workshop on Cryptography for the Internet of Things Jens Hermans KU

Privacy-Preserving Statistical Data Analysis on Federated Databases Dan Bogdanov Liina Kamm

Privacy Preserving Data Mining: Additive Data Perturbation Outline Input perturbation

pSTAIX A Process-Aware Architecture to Support Research Processes Marius Politze, Bernd

Implementation of the file system layer in HelenOS XXXII. Conference EurOpen.CZ Jakub Jermar

welcome to production Graeme Foster Spanish Software Developer 5 years ago, I co-designed,

Trusted Architecture for Secure Shared Services (with Privacy) Sampo Kellomki (sampo@zxidp.org)

Introduction to Building the IoT with P2P &amp; Niels Olof Bouvin 1 Overview Introduction

6.888: Lecture 2 Data Center Network Architectures Mohammad Alizadeh Spring 2016 Slides

Datacenter Networks Justine Sherry &amp; Peter Steenkiste 15-441/641 Administrivia P3 CP1

CS 744: Big Data Systems Shivaram Venkataraman Fall 2018 With slides from Mosharaf Chowdhury

DIMACS/PORTIA Workshop on Privacy Preserving Data Mining Data Mining & Information Privacy:

Introduction to Building the IoT with P2P & Niels Olof Bouvin 1 Overview Introduction

Datacenter Networks Justine Sherry & Peter Steenkiste 15-441/641 Administrivia P3 CP1