Annotations on Document Previews

Introduction

Location-specific feedback has always been fundamental to collaboration. At Dropbox, we’ve recognized this need and implemented annotations on document previews. Our goal was to allow users to provide focused and clear feedback by drawing rectangles and highlighting text on their documents. We ran into a few main challenges along the way: How do we ensure annotations can be drawn and rendered accurately on any kind of document, with any viewport size, and using any platform? How can we maintain isolation of user documents for security? How can we keep performance smooth and snappy?

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Infrastructure Update: Pushing the edges of our global performance

Dropbox has hundreds of millions of registered users, and we’re always hard at work to ensure our customers have a speedy, reliable experience, wherever they are. Today, I am excited to announce an expansion to our global infrastructure that will deliver faster transfer speeds and improved performance for our customers around the world.

To give all of our users fast, reliable network performance, we’ve launched new Points of Presence (PoPs) across Europe, Asia, and parts of the US. We’ve coupled these PoPs with an open-peering policy, and as a result have seen consistent speed improvements.

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How Dropbox securely stores your passwords

It’s universally acknowledged that it’s a bad idea to store plain-text passwords. If a database containing plain-text passwords is compromised, user accounts are in immediate danger. For this reason, as early as 1976, the industry standardized on storing passwords using secure, one-way hashing mechanisms (starting with Unix Crypt). Unfortunately, while this prevents the direct reading of passwords in case of a compromise, all hashing mechanisms necessarily allow attackers to brute force the hash offline, by going through lists of possible passwords, hashing them, and comparing the result. In this context, secure hashing functions like SHA have a critical flaw for password hashing: they are designed to be fast.

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Fast and Accurate Document Detection for Scanning

A few weeks ago, Dropbox launched a set of new productivity tools including document scanning on iOS. This new feature allows users to scan documents with their smartphone camera and store those scans directly in their Dropbox. The feature automatically detects the document in the frame, extracts it from the background, fits it to a rectangular shape, removes shadows and adjusts the contrast, and finally saves it to a PDF file. For Dropbox Business users, we also run Optical Character Recognition (OCR) to recognize the text in the document for search and copy-pasting.

Beginning today,

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Lepton image compression: saving 22% losslessly from images at 15MB/s

We are pleased to announce the open source release of Lepton, our new streaming image compression format, under the Apache license.

Lepton achieves a 22% savings reduction for existing JPEG images, by predicting coefficients in JPEG blocks and feeding those predictions as context into an arithmetic coder. Lepton preserves the original file bit-for-bit perfectly. It compresses JPEG files at a rate of 5 megabytes per second and decodes them back to the original bits at 15 megabytes per second, securely, deterministically, and in under 24 megabytes of memory.

We have used Lepton to encode 16 billion images saved to Dropbox,

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