Facebook, Inc.

Meta Platforms, Inc.

Google Inc.

Jonathan H Frank

Yigal Dan Rubinstein

Jacob Andrew Brill

Arturo Bejar

David Breger

Allan Stewart

Matthew Knight Jones

Christopher William Palow

Andrei Bajenov

Colvin Pitts

Ariel Braunstein

Alok Menghrajani

Julio Cesar Hernandez Zaragoza

Alex Song

Orin Green

Alok Menghranjani

Steve Cooper

Tim Milliron

Yusuke Yasui

Saeid Shahhosseini

Bipeng Zhang

A social networking system performs account recovery for a user with the help of the user's connections (e.g., friends). The social networking system selects connections of the user based on information indicating likelihood of real-world interactions between the user and the selected connections. Access codes are sent to the selected connections and the user instructed to obtain access codes from the selected connections via a communication that is outside the social networking system, for example, via phone. The user provides the access codes obtained from the selected connections to the social networking system. If the access codes provided by the user match the access codes sent to the selected connections, the user is granted access to the account. Real-world interactions between two users are determined based on sharing of devices between the users or information indicating presence of the users in the same place during same time interval.

Using social graph for account recovery

A social networking system identifies relationships between friends of a target user that are likely to be unexpected to the target user. To identify an unexpected relationship among a user's friends, the social networking system determines a measure of unexpectedness for pairs of connections of the target user and selects pairs of connections for presentation to the user based on the measure of unexpectedness. The measure of unexpectedness of a relationship between a pair of friends is inversely related to a number of connections between each of the pair of friends and the target user. Information describing the pair of unexpected friends may be presented to a target user along with content relating the two friends, such as photos in which both friends are tagged, events attended by the unexpected friends together, or places both unexpected friends checked-in at the same time.

Identifying unexpected relationships in a social networking system

A combined video of a scene may be generated for applications such as virtual reality or augmented reality. In one method, a camera system may be oriented at a first orientation and used to capture first video of a first portion of the scene. The camera system may then be rotated to a second orientation and used to capture second video of a second portion of the scene that is offset from the first portion such that the first video and the second video each have an overlapping video portion depicting an overlapping portion of the scene in which the first portion and the second portion of the scene overlap with each other. The first and second portions may be combined together to generate the combined video, which may depict the first and second portions substantially without duplicative inclusion of the overlapping video portion.

Wedge-based light-field video capture

In one embodiment, a computing device determines a Completely Automated Public Turing Test to Tell Computers and Humans Apart (CAPTCHA). The CAPTCHA includes a first static image that has image sections that are arranged in a first order. Each of the image sections corresponds to a unique identifier. The CAPTCHA further includes a second static image that includes each of the image sections of the first static image that are arranged in a second order. The computing device generates web-browser-executable code for converting the second static image to the first static image based on the first static image, the first order, and the unique identifiers. The computing device sends the second static image and the web-browser-executable code to a client device.

Captcha image scramble

User login information submitted as part of an attempt to log into a computer system is evaluated for unauthorized or illegitimate use based on indicators of suspicious behavior. Example indicators of suspicious behavior include whether the login information is known to have been compromised, whether the login attempt originates from a network source or a physical source that has previously originated an attempt to log in using login information known to have been compromised, and whether multiple login attempts using the login information from multiple users has originated from the source. A suspicion index can be calculated based on the presence of the indicators of suspicious behavior. The system can require enhanced authentication based on the measurement of suspicious behavior.

Preventing unauthorized account access using compromised login credentials

Predicting real-world connections based on interactions in social networking system

In one embodiment, a client computing device receives information regarding a Completely Automated Public Turing Test to Tell Computers and Humans Apart (CAPTCHA). The CAPTCHA includes an image file, a challenge, and code that is executable by a web browser to unscramble the received image file. The code includes instructions to divide the received image file into image sections, each image section having a unique identifier and grouped into either a first set or a second set. The code further contains instructions to transpose each image section in the first set into a new position, creating a new image. A web browser of the client computing device executes the code to create a second image from the received image file. The second image and the challenge are presented to a user of the client computing device.

CAPTCHA image scramble

Particular embodiments determine a modified image for a CAPTCHA. The CAPTCHA may include an original image, a challenge based on the original image, and/or a correct response based on the original image. The modified image may be a scrambled version of the original image. Web-browser-executable code is determined for unscrambling the modified image back to the original image. The modified image and the web-browser-executable code are then provided to a computing device. Upon receiving the modified image and the web-browser-executable code, the computing device then displays the original image based on the modified image and the web-browser-executable code.

Locating social networking system accounts for user of the social networking system permits the users to locate and access their accounts even if they cannot provide a user login ID or a login email address associated with their social networking system account. The social networking system locates a user account by receiving a user name associated with the user and a friend name of a friend connected to the user in the social networking system and identifying a user account wherein the identified user account has a user name matching the received user name and the identified user account is connected with another user in the social networking system who has a user name matching the received friend name.

Identifying a user account in a social networking system

In one embodiment, accessing a first image of a CAPTCHA, wherein the CAPTCHA comprises: the first image; a challenge based on the first image; and a correct response based on the first image; constructing a second image by scrambling the first image, comprising: cutting the first image into a plurality of image sections; recording positions of the image sections in the first image; and randomly rearranging the image sections to construct the second image; generating web-browser-executable code for unscrambling the second image back to the first image, wherein the web-browser-executable code indicates, for each one of the image sections in the second image, the position of the image section in the first image; and transmitting the second image and the web-browser-executable code to a second computing device.

Growing community of inventors

Mountain View, CA, United States of America

Jonathan H Frank