Hewlett Packard Enterprise Development LP

Hewlett-packard Development Company, L.p.

Intertrust Technologies Corporation

Micro Focus Lcc

Entit Software LLC

Ent. Services Development Corporation LP

Surety, LLC

Stuart Haber

William G Horne

Tomas Sander

Pratyusa Kumar Manadhata

Binyamin Pinkas

Prasad V Rao

Robert E Tarjan

Liqun Chen

Miaomiao Zhang

Geoffrey Ndu

John Thomas Brassil

Christopher L Dalton

Adrian Shaw

Miranda Jane Felicity Mowbray

Albert John Wettlaufer

Wes Doonan

Amro J Awad

Rone H Lewis

Ravi Arun Netravali

Sandeep Yadav

Marc R Eisenbarth

Danfeng Yao

Liu Yang

According to an example, key splitting may include utilizing a masked version of a master key that is masked by using a mask.

Key splitting

Examples disclosed herein relate to data objects associated with private set intersection (PSI). Some examples disclosed herein may enable identifying a set of server elements and a set of data objects. Each data object of the set of data objects may be associated with at least one server element of the set of server elements. Some examples further enable sending the set of server elements and the set of data objects to a client computing device that has a set of client elements. A private set intersection (PSI) between the set of server elements and the set of client elements may be inaccessible by the client computing device, and a subset of the set of data objects that are associated with the PSI may be accessible by the client computing device.

Data objects associated with private set intersection (PSI)

Examples relate to Input/Output (I/O) data encryption and decryption. In an example, an encryption/decryption engine on an Integrated Circuit (IC) of a computing device obtains at least one plaintext data. Some examples determine, by the encryption/decryption engine, whether the at least one plaintext data is to be sent to a memory in the computing device or to an I/O device. Some examples apply, when the at least one plaintext data is to be sent to the I/O device and by the encryption/decryption engine, an encryption primitive of a block cipher encryption algorithm to the at least one plaintext data to create output encrypted data, wherein an initialization vector that comprises a random number is applied to the encryption primitive.

Input/output data encryption

In one implementation, a redactable document signature system includes an encoding engine, a reordering engine, and a signature engine. The encoding engine is to access a plurality of subdocuments of a document, to generate a plurality of commitment values from the plurality of subdocuments, and to generate a plurality of dummy values. Each dummy value is indistinguishable from a commitment value. The reordering engine is to define an order of the plurality of commitment values and the plurality of dummy values independent of an order of the subdocuments. The signature engine is to calculate a signature value for the document using the plurality of commitment values and the plurality of dummy values according to the order.

Redactable document signatures

A technique includes receiving a request to initialize a region of a memory. Content that is stored in the region is encrypted based at least in part on a stored nonce value and a key. The technique includes, in response to the request, performing cryptographic-based initialization of the memory, including altering the stored nonce value to initialize the region of the memory.

Cryptographic-based initialization of memory content

A method of establishing a secure channel between a human user and a computer application is described. A secret unique identifier ('PIN') is shared between a user and an application. When the user makes a request that involves utilizing the PIN for authentication purposes, the application renders a randomly selected identifier. The randomly selected identifier is in a format that is recognizable to a human but is not readily recognizable by an automated agent. The randomly selected identifier is then presented to the human user. The user identifies the relationship between the randomly selected identifier and the PIN. If the user's input reflects the fact that the user knows the PIN, then the user is authenticated.

Establishing a secure channel with a human user

A blockchain includes blocks that each store a hash value computed using a hash function from data of the block. Another hash value is computed for each block using a different hash function, and added to the block within the blockchain. New blocks subsequently added to the blockchain have hash values computed using just the different hash function.

Blockchain hash value recomputation

In one implementation, a physical version of a document is converted to a digital representation of the physical version and a new certificate is computed for the digital representation of the physical version. The new certificate is computed based on the digital representation of the physical version, at least one processing step performed on the digital representation, and a prior certificate computed for a prior digital representation indicative of the physical version. In another implementation, a document is validated.

Computing new certificate for digitized version of a physical document

A method for submatch extraction may include receiving an input string, receiving a regular expression. The method may further include converting the regular expression with capturing groups into ordered binary decision diagrams (OBDDs) to extract submatches.

Submatch extraction

A method for authenticating a user's location in a femtocell-based network is disclosed. A user is associated to a femtocell connected to a connection point in the wireless network. An indication of the user's location is provided to a remote user. A characteristic of a connection between the femtocell and the connection point is monitored. The monitored characteristic is provided to the remote user to verify user's location.

Authenticating a user's location in a femtocell-based network

A method for submatch extraction may include receiving an input string, receiving a regular expression, and converting the regular expression with capturing groups into a plurality of finite automata to extract submatches. The method further includes using a first automaton to determine whether the input string is in a language described by the regular expression, and to process the input string, and using states of the first automaton in a second automaton to extract the submatches.

Systems, computer-readable media storing instructions, and methods can infer a state of behavior. Such a method can include constructing a graph including nodes representing hosts and domains based on an event dataset. The graph can be seeded with information external to the event dataset. A belief whether each of the nodes is in a particular state of behavior can be calculated based on marginal probability estimation.

Inferring a state of behavior through marginal probability estimation

A method of establishing the integrity of an audit record set is described. The method comprises receiving a set of audit records and generating a first set of random values wherein each audit record in the set corresponds to at least one value of the first set. The method further comprises generating a second set of values based on an audit record and a corresponding value of the first set for each audit record in the set and generating a summary value based on the second set of values. The method further comprises certifying the summary value to generate an integrity certificate enabling verification of the integrity of the audit record set and storing the audit record set and at least one of the first set of values and the generated digital signature.

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New York, NY, United States of America

Stuart Haber