Abusing cloud-based browsers for fun and profit

Cloud services have become a cheap and popular means of computing. They allow users to synchronize data between devices and relieve low-powered devices from heavy com-putations. In response to the surge of smartphones and mobile devices, several cloud-based Web browsers have be-come commercially available. These “cloud browsers ” as-semble and render Web pages within the cloud, executing JavaScript code for the mobile client. This paper explores how the computational abilities of cloud browsers may be ex-ploited through a Browser MapReduce (BMR) architecture for executing large, parallel tasks. We explore the computa-tion and memory limits of four cloud browsers, and demon-strate the viability of BMR by implementing a client based on a reverse engineering of the Puffin cloud browser. We implement and test three canonical MapReduce applications (word count, distributed grep, and distributed sort). While we perform experiments on relatively small amounts of data (100 MB) for ethical considerations, our results strongly sug-gest that current cloud browsers are a viable source of arbi-trary free computing at large scale