Cisco Technology, Inc.

Intuit, Inc.

Sun Microsystems, Inc.

Palo Alto Research Center Inc.

Oracle America, Inc.

Oracle International Corporation

Cisco Systems Inc.

Intuti, Inc.

Glenn Carter Scott

Christopher A Wood

Michael R Gabriel

Germano Caronni

Roger Charles Meike

Priya Mahadevan

Ignacio Solis

Amit Narayan Gupta

Raphael J Rom

Christoph L Schuba

Tom R Markson

Marc E Mosko

Sandeep Kumar

Parikshit Lingampally

Ian Maya Panchevre

Martin Patterson

Geoffrey Mulligan

Geoffrey G Baehr

Kevin C Fox

Michael Richard Gabriel

Ashar Aziz

Ersin Uzun

Thomas L Lyon

Ian Pentland

Andriana Ioannou

Carolyn Turbyfill

William Danielson

William J Raduchel

Randall B Smith

Timothy G Lindholm

Michael F Plass

Reema Koo

Sandeep Kulmar

Induprakas Keri

Amir Eftekhari

John C Tang

Amir R Eftekhari

Ian Barry Crabtree

Robert P St Pierre

Robert F Tow

Esme Manandise

Vipul Gupta

Kevin Michael Furbish

Esmé Manandise

Lalla Mouatadid

Priti Goel

Alan Walendowski

Rachel Jack

Giruba Beulah Se

Maria Kissa

Benjamin J Stoltz

Mike Gabriel

Roger Meike

Ian B Crabtree

A method converts from compressed language to natural language. The method includes receiving an element string. The element string is in a compressed language format and is extracted from a document in a structured document language. The method includes tokenizing the element string to form multiple element tokens, generating a token set from the element tokens, and generating a name string from multiple token sets. The name string is in a natural language format.

Converting from compressed language to natural language

A method extracts explainable corpora embeddings. The method includes constructing a graph with nodes representing terms from a text sequence and edges that include pointwise values generated between pairs of terms. The method further includes generating a rank vector from the graph. Elements of the rank vector correspond to the edges of the graph. A rank value, of the rank values, corresponds to a term from the text sequence. The method further includes selecting the term by comparing the rank vector to a previous rank vector generated for a previous text sequence.

Extracting explainable corpora embeddings

A method optimizes questions to retain engagement. The method includes generating, using a machine learning model, a churn risk from user interaction data. The method includes selecting, when the churn risk satisfies a threshold, a field, from multiple fields, using multiple prediction confidences corresponding to multiple prediction values generated for the multiple fields. The method includes obtaining a prediction value for the field and obtaining a question, corresponding to the field, using the prediction value. The method includes presenting the question and receiving a user input in response to the question.

Optimizing questions to retain engagement

A method services competing updates from multiple servicing instances. An update message is received by a class of a plurality of classes that service an object. The update message includes an update to the object and an expected version for the object. A version match is determined between the expected version and a current version of the object. When the version match is successful, the update is applied to the object. A response message including the current version of the object is generated. The response message is transmitted. When the update is successfully applied, the response message is transmitted as a success message. When the update is not successfully applied, the response message is transmitted as a failure message.

Competing updates from multiple servicing instances

A method including transforming metrics, related to a computer network environment, into a digital image including pixels that represent the metrics. The computer network environment initially is load balanced by a first load balancing scheme selected from among load balancing schemes. The method also includes generating a classification of the digital image. The method also includes selecting, based on the classification of the digital image, a selected load balancing scheme from among the load balancing schemes. The method also includes changing the first load balancing scheme to the selected load balancing scheme such that the selected load balancing scheme is applied to the computer network environment.

Optimizing selection and dynamic configuration of load balancing techniques to resist cyber attacks

A method secures hash chains via hybrid consensus. A proximate payload for a proximate chain block for a proximate chain is obtained. A first identifier of the proximate chain and the proximate payload are hashed with a hash function to generate a second identifier of the proximate chain. The proximate chain block is added to the proximate chain. The proximate chain block includes the first identifier, the second identifier, and the proximate payload. A request to add the second identifier to a reporting chain is transmitted. A response indicating that the second identifier is incorporated into the reporting chain using the consensus mechanism is received.

Securing hash chains via hybrid consensus

A method for using shareable and nested transaction on hash chains includes storing transaction data of a transaction of a hash chain. A lock block is appended to the hash chain. Appending the lock block includes setting a tail block identifier of the hash chain from a preceding tail block of a preceding transaction to the lock block. A data block is appended to the hash chain. Appending the data block includes setting the tail block identifier of the hash chain to the data block. The method further includes removing the transaction data from the transaction without invalidating the hash chain. The method further includes appending an updated data block to the hash chain to update the transaction with updated transaction data.

Shareable and nested transactions on hash chains

A method implements anonymous uncensorable cryptographic chains. The method includes receiving, from a first application, verifiable data for a current record and unverified data for the current record. The unverified data for the current record was received by the first application from a second application. The method further includes verifying the verifiable data for the current record with unverified data from a previous record. The method further includes recording the verifiable data for the current record and the unverified data for the current record to the current record responsive to verifying the verifiable data for the current record. The method further includes presenting the current record to one or more of the first application and to the second application.

Anonymous uncensorable cryptographic chains

The present disclosure relates to a trustworthy data exchange. Embodiments include receiving, from a device, a query, wherein the query comprises a question. Embodiments include identifying particular information related to the query. Embodiments include receiving credentials from a user for retrieving the particular information related to the query. Embodiments include retrieving, using the credentials, the particular information related to the query from one or more data repositories that are part of a distributed database comprising an immutable data store that maintains a verifiable history of changes to information stored in the distributed database. Embodiments include determining, based on the particular information related to the query, an answer to the query. Embodiments include providing the answer to the device.

Trustworthy data exchange using distributed databases

Certain aspects of the present disclosure provide techniques for summarizing data in a distributed system. Embodiments include generating an ordered list of blocks by iterating through a first group of blocks of a hash chain starting at a last block of the hash chain and adding each of the first group of blocks of the hash chain to the ordered list. Embodiments further include generating summary data by applying a summary function to the first group of blocks based on the ordered list. The summary function may take the ordered list as an input and provide the summary data of the first group of blocks as an output. Embodiments further include generating a summary block comprising the summary data and adding the summary block to a summary chain.

Summary chains in distributed systems

Techniques are disclosed for managing workflows using block chains. An entire workflow may be stored as a finite state machine on a block chain. Each data block of the block chain may correspond to a state and related operation of a workflow. Each data block of the block chain may be used as an input to a subsequent state of the workflow. Thus, any input may be used to compute the workflow even if the input is not designed to be used by a workflow. Nested block chains, each corresponding to a different workflow or different part of a workflow may be used to increase performance of computing the workflows.

Workflow management via block chains

Techniques are disclosed for managing encrypted data stored in one or more blocks of a first data structure. One embodiment presented herein includes a computer-implemented method, which includes retrieving the encrypted data from the one or more blocks. The method further includes placing the encrypted data in a container object. The method further includes applying an encryption technique to the container object to generate an encrypted container object and a key. The method further includes generating a second data structure. A first block of the second data structure may include either the encrypted container object or information related to the encrypted container object.

Re-encrypting data on a hash chain

The present disclosure relates to generating composite user identities in a distributed computing system. According to one embodiment, an example method generally includes transmitting, to a plurality of identity providers, a request for user identity information. A service provider receives, from a subset of the plurality of identity providers, the user identity information and selects a subset of the received user identity information to be used in verifying an identity of a user based, at least in part, on a reputation score associated with each identity provider in the subset of identity providers. The service provider generates a composite user identity based on the selected subset of the received user identity information. The service provider takes one or more actions to enable use of a service based on the generated composite user identity.

Composite user identities in distributed computing systems

A replica management system facilitates maintaining a distributed and fault-tolerant state for a variable over an Information Centric Network (ICN) by replicating the variable across a set of ICN nodes. During operation, a variable-hosting ICN node can receive an Interest that includes a value-updating command for a replica instance of the variable, current values for a set of replicas of the variable, and a new value for the variable. The ICN node can determine, based on the current values for the set of replica variables, whether the current value for the local replica variable is an authoritative value. If so, the ICN node updates the local replica variable to the new value. However, if the current local value is not the authoritative value, the ICN node rolls back a state of the local replica variable to a previous state, and updates the local replica variable to the new value.

System and method for maintaining a distributed and fault-tolerant state over an information centric network

Growing community of inventors

Los Altos, CA, United States of America

Glenn Carter Scott