Abstract

Online advertising is a major economic force in the Internet today. Today’s deployments, however, increasingly erode user privacy as advertising companies like Google increasingly target users. In this talk, we suggest that it is possible to build an advertising system that fits well into the existing online advertising business model, targets users extremely well, is very private, and scales well. The key to our approach is adware: client computers run a local software agent that profiles the user, requests the appropriate ads, displays the locally, and reports on views and clicks, all while preserving privacy. This talk outlines the system design, and discusses its pros and cons.

Bio:

Paul Francis is a tenured faculty at the Max Planck Institute for Software Systems in Germany. Paul has held research positions at Cornell University, ACIRI , NTT Software Labs, Bellcore,and MITRE , and was Chief Scientist at two Silicon Valley startups. Paul’s research centers around routing and addressing problems in the Internet and P2P networks. Paul’s innovations include NAT , shared-tree multicast, the first P2P multicast system, the first DHT (as part of landmark routing), and Virtual Aggregation. These days, Paul is wondering why so much of our private data is being held in the cloud.