Multi-Party Trust Computation in Decentralized Environments

In this paper, we describe a decentralized privacy-preserving protocol for securely casting trust ratings in distributed reputation systems. Our protocol allows n participants to cast their votes in a way that preserves the privacy of individual values against both internal and external attacks. The protocol is coupled with an extensive theoretical analysis in which we formally prove that our protocol is resistant to collusion against as many as n-1 corrupted nodes in the semi-honest model. The behavior of our protocol is tested in a real P2P network by measuring its communication delay and processing overhead. The experimental results uncover the advantages of our protocol over previous works in the area; without sacrificing security, our decentralized protocol is shown to be almost one order of magnitude faster than the previous best protocol for providing anonymous feedback.

Design as Symbolic Violence. Design for Social Justice.

Design embeds ideas in communication and artefacts in subtle and psychologically powerful ways. Sociologist Pierre Bourdieu coined the term ‘symbolic violence’ to describe how powerful ideologies, priorities, values and even sensibilities are constructed and reproduced through cultural institutions, processes and practices. Through symbolic violence, individuals learn to consider unjust conditions as natural and even come to value customs and ideas that are oppressive. Symbolic violence normalises structural violence and enables real violence to take place, often preceding it and later justifying it. Feminist, class, race and indigenous scholars and activists describe how oppressions (how patriarchy, racism, colonialism, etc.) exist within institutions and structures, and also within cultural practices that embed ideologies into everyday life. The theory of symbolic violence sheds light on how design can function to naturalise oppressions and then obfuscate power relations around this process. Through symbolic violence, design can function as an enabler for the exploitation of certain groups of people and the environment they (and ultimately ‘we’) depend on to live. Design functions as symbolic violence when it is involved with the creation and reproduction of ideas, practices, tools and processes that result in structural and other types of violence (including ecocide). Breaking symbolic violence involves discovering how it works and building capacities to challenge and transform dysfunctional ideologies, structures and institutions. This conversation will give participants an opportunity to discuss, critique and/or develop the theory of design as symbolic violence as a basis for the development of design strategies for social justice.

Secure and Scalable Statistical Computation of Questionnaire Data in R

Collecting data via a questionnaire and analyzing them while preserving respondents’ privacy may increase the number of respondents and the truthfulness of their responses. It may also reduce the systematic differences between respondents and non-respondents. In this paper, we propose a privacy-preserving method for collecting and analyzing survey responses using secure multi-party computation (SMC). The method is secure under the semi-honest adversarial model. The proposed method computes a wide variety of statistics. Total and stratified statistical counts are computed using the secure protocols developed in this paper. Then, additional statistics, such as a contingency table, a chi-square test, an odds ratio, and logistic regression, are computed within the R statistical environment using the statistical counts as building blocks. The method was evaluated on a questionnaire dataset of 3,158 respondents sampled for a medical study and simulated questionnaire datasets of up to 50,000 respondents. The computation time for the statistical analyses linearly scales as the number of respondents increases. The results show that the method is efficient and scalable for practical use. It can also be used for other applications in which categorical data are collected.