A Web Future of Computation

Crowdsourcing. Social Machines. Human computation. Co-construction Made Real

INFO6003 (2013) Towards a formal framework for computation trust -- paper

the introduction of this research paper (especially pg 2-4) and its list of references may be useful to clarify the notions of Bayesian learning applied to trust as explained in the lectures. This is optional reading

WAIS Seminar:Secure Multi-Party Computation for the Masses

Speaker(s): Prof. David Evans Organiser: Dr Tim Chown Time: 22/05/2014 10:45-11:45 Location: B53/4025 Abstract Secure multi-party computation enables two (or more) participants to reliably compute a function that depends on both of their inputs, without revealing those inputs to the other party or needing to trust any other party. It could enable two people who meet at a conference to learn who they known in common without revealing any of their other contacts, or allow a pharmaceutical company to determine the correct dosage of a medication based on a patient’s genome without compromising the privacy of the patient. A general solution to this problem has been known since Yao's pioneering work in the 1980s, but only recently has it become conceivable to use this approach in practice. Over the past few years, my research group has worked towards making secure computation practical for real applications. In this talk, I'll provide a brief introduction to secure computation protocols, describe the techniques we have developed to design scalable and efficient protocols, and share some recent results on improving efficiency and how secure computing applications are developed.