Conclave: secure multi-party computation on big data (extended TR)

Secure Multi-Party Computation (MPC) allows mutually distrusting parties to run joint computations without revealing private data. Current MPC algorithms scale poorly with data size, which makes MPC on "big data" prohibitively slow and inhibits its practical use. Many relational analytics queries can maintain MPC's end-to-end security guarantee without using cryptographic MPC techniques for all operations. Conclave is a query compiler that accelerates such queries by transforming them into a combination of data-parallel, local cleartext processing and small MPC steps. When parties trust others with specific subsets of the data, Conclave applies new hybrid MPC-cleartext protocols to run additional steps outside of MPC and improve scalability further. Our Conclave prototype generates code for cleartext processing in Python and Spark, and for secure MPC using the Sharemind and Obliv-C frameworks. Conclave scales to data sets between three and six orders of magnitude larger than state-of-the-art MPC frameworks support on their own. Thanks to its hybrid protocols, Conclave also substantially outperforms SMCQL, the most similar existing system.Comment: Extended technical report for EuroSys 2019 pape

Discursive Exit

Some women did not participate in the Women’s March, rejecting its claims of unity and solidarity because white women mobilize only in their self-interest. This is a form of exit with three features: (1) rejecting a political claim; (2) providing reasons to the power-wielder and the broader public; (3) demanding accountability both as sanction and as deliberation, which requires a discussion about the claim – in this case, the meaning of the group and the terms on which it understands itself. This combination of exit, voice, and deliberative accountability might accurately be called ‘discursive exit.’ Discursive exit addresses conceptual and normative limitations of standard accounts of exit, voice, and loyalty, in particular, when exit and voice are imperfect — because exit can be seen as disapproval of an entire cause — and morally problematic — because voice ‘from within’ implies that cause trumps disagreement, leaving people morally complicit in an unwelcome exercise of power

Trade Potential and UN Peacekeeping Participation

The determinants of a country's UN peacekeeping troop contribution have been persistently studied. Trade, as a crucial self-interest motivation, is one of the important explanatory variables in the extant literature. However, the existing literature presents mixed results on the influence of trade on peacekeeping troop contributions. To capture the effect of trade on contributions precisely, we need to model expectations about future trade volume in a better way. Countries are pressured by the economic and political risks caused by the trade disruption and lobby groups to send peacekeeping troops to enable future trade or secure future investments. Therefore, trade potential, rather than realized trade, drives peacekeeping troop contributions. A gravity model is used to measure the trade potential between the UN peacekeeping mission countries and contributors, and test its relationship with the UN peacekeeping participation. Based on this measurement and a dyadic troop contribution dataset covering the period from 1990 to 2012, this article demonstrates that the counter-factual predictive trade volume is a relevant predictor of UN peacekeeping troop contributions