Intel Corporation

Mcafee, Inc.

Omer Ben-Shalom

Alex Nayshtut

Ned M Smith

Oleg Pogorelik

Igor G Muttik

Eran Birk

Sigal Louchheim

Hong C Li

Glen J Anderson

Tobias Max Kohlenberg

Jennifer Anne Healey

Mubashir A Mian

Keith L Shippy

Adi Shaliv

Tamara Gaidar

Manish Dave

Hormuzd M Khosravi

Giuseppe Beppe Raffa

Timothy Verrall

Lenitra M Durham

Tarun Viswanathan

Dennis M Morgan

Stephen R Brown

Kathy Yuen

Richard T Beckwith

Uri Blumenthal

Jamie Sherman

David M Durham

Rajesh Poornachandran

Reshma Lal

Prashant Dewan

Michael E Kounavis

Pradeep M Pappachan

Igor Tatourian

Vadim Sukhomlinov

Avigdor Dori Eldar

Moshe Maor

Shlomo Avital

Steve J Brown

Yosi Govezensky

Ariel Moshkovitz

Edward V Jimison, Jr

Terry H Yoshii

Joshua Ekandem

Michal Jacob

Yaniv Avidan

Shai Skavas Kavas

Raizy Kellermann

Denis Klimov

Shachaf Levi

Gyora M Benedek

Michael Raziel

Ido Lapidot

Dror Shilo

Gaurav Kumar

Guy Ben-Artzi

Dan Horovitz

Shay Pluderman

Omri Barkay

Yoni Wolf

Antonios Papadimitriou

Elisheva Zobin

Oren Galler

Victoria Almog-Ayzenberg

Miriam Engel

Ezra Caltum

Guy Barnhart-magen

Alan Tatourian

Barry R Pivitt

Oren Duenias

Ayelet Naor

Hila Yitzhaki

Yoram Hassidim

Behnam Eliyahu

Tzipi Wales

Hong Li

Richard Beckwith

Edward V Jimison Jr

Technologies for audiovisual communication include an audiovisual server and a number of audiovisual client devices, including a presenter device and a number of audience devices. Each audience device captures an audiovisual stream and transmits the audiovisual stream to the audiovisual server. Each audience device also captures sensor input data such as eye tracking data or facial expression data and transmits abstracted sensor input data to the audiovisual server. The abstracted sensor input data may be based on the captured audiovisual stream. The audiovisual server determines an interestingness rating associated with each audience device based on the sensor input data, and selects one or more audiovisual streams based on the interestingness ratings. The audiovisual server transmits the selected audiovisual streams to the presenter device. The audiovisual server may update the interestingness rating algorithm based on feedback from the presenter device or the audience devices. Other embodiments are described and claimed.

Technologies for audiovisual communication using interestingness algorithms

The disclosure generally relates to method, system and apparatus for privacy enhancement mode for integrated cameras. In an exemplary embodiment, the disclosure allows a user of a device equipped with an integrated device to engage the device in the so-called privacy mode whereby while the camera is engaged, the device does not broadcast the user's images; rather the device uses the camera to detect, discern and determine the user's attributes. Such attributes may include one or more of movement, motion, mood, gesture and temperature of the user. The attributes may include specificities of the user's environment.

Method, system and apparatus for privacy enhancement mode for integrated cameras

Methods, apparatuses and system provide for technology that interleaves a plurality of verification commands with a plurality of copy commands in a command buffer, wherein each copy command includes a message authentication code (MAC) derived from a master session key, wherein one or more of the plurality of verification commands corresponds to a copy command in the plurality of copy commands, and wherein a verification command at an end of the command buffer corresponds to contents of the command buffer. The technology may also add a MAC generation command to the command buffer, wherein the MAC generation command references an address of a compute result.

Graphics security with synergistic encryption, content-based and resource management technology

Techniques and apparatuses to harden AI systems against various attacks are provided. Among the different techniques and apparatuses, is provided, techniques and apparatuses that expand the domain for an inference model to include both visible classes and well as hidden classes. The hidden classes can be used to detect possible probing attacks against the model.

Securing systems employing artificial intelligence

Machine learning fraud resiliency using perceptual descriptors is described. An example of a computer-readable storage medium includes instructions for accessing multiple examples in a training dataset for a classifier system; calculating one or more perceptual hashes for each of the examples; generating clusters of perceptual hashes for the multiple examples based on the calculation of the one or more perceptual hashes for each of the plurality of examples; obtaining an inference sample for classification by the classifier system; generating a first classification result for the inference sample utilizing a neural network classifier and generating a second classification result utilizing the generated clusters of perceptual hashes; comparing the first classification result with the second classification result; and, upon a determination that the first classification result does not match the second classification result, determining a suspicion of an adversarial attack.

Machine learning fraud resiliency using perceptual descriptors

The disclosure generally relates to method, system and apparatus for multifactor authentication exchange using out of band communication to authenticate a user while defending against the man in the middle attack. In an exemplary method, the disclosed principles provide a multifactor authentication (MFA) exchange, which includes: receiving an authentication request through in-band communication from a first device associated with a user to authenticate the user, the authentication request including a first authentication factor to identify the user; generating a second authentication factor, the second authentication factor further comprising an authorization token; generating an encryption key to encrypt the authorization token and a redirect Uniform Resource Locator (URL) address; and communicating the second authentication factor, the encryption key and the redirect URL address to a second device associated with the user.

Method, system and apparatus for protecting access tokens created by multifactor authentication

Technologies for secure collective authorization include multiple computing devices in communication over a network. A computing device may perform a join protocol with a group leader to receive a group private key that is associated with an interface implemented by the computing device. The interface may be an instance of an object model implemented by the computing device or membership of the computing device in a subsystem. The computing device receives a request for attestation to the interface, selects the group private key for the interface, and sends an attestation in response to the request. Another computing device may receive the attestation and verify the attestation with a group public key corresponding to the group private key. The group private key may be an enhanced privacy identifier (EPID) private key, and the group public key may be an EPID public key. Other embodiments are described and claimed.

Technologies for collective authorization with hierarchical group keys

A circuit includes a first communication interface configured to receive first sensor data from a stationary sensor. The first sensor data include a result of a first sensing of a local environment of the stationary sensor performed by the stationary sensor. The circuit may further include a second communication interface configured to receive second sensor data from an unmanned aerial vehicle. The second sensor data include a result of a second sensing of at least a portion of the local environment of the stationary sensor performed by a sensor of the unmanned aerial vehicle. The circuit may further include one or a plurality of processors configured to compare the first sensor data and the second sensor data and to classify the at least one stationary sensor based on a result of the comparison.

Method, a circuit and a system for environmental sensing

Technologies to facilitate supervision of an online identify include a gateway server to facilitate and monitor access to an online service by a user of a 'child' client computer device. The gateway server may include an identity manager to receive a request for access to the online service from the client computing device, retrieve access information to the online service, and facilitate access to the online service for the client computing device using the access information. The access information is kept confidential from the user. The gateway server may also include an activity monitor module to control activity between the client computing device and the online service based on the set of policy rules of a policy database. The gateway server may transmit notifications of such activity to a 'parental' client computing device for review and/or approval, which also may be used to update the policy database.

Supervised online identity

The present disclosure is directed to systems and methods for the selective introduction of low-level pseudo-random noise into at least a portion of the weights used in a neural network model to increase the robustness of the neural network and provide a stochastic transformation defense against perturbation type attacks. Random number generation circuitry provides a plurality of pseudo-random values. Combiner circuitry combines the pseudo-random values with a defined number of least significant bits/digits in at least some of the weights used to provide a neural network model implemented by neural network circuitry. In some instances, selection circuitry selects pseudo-random values for combination with the network weights based on a defined pseudo-random value probability distribution.

Defending neural networks by randomizing model weights

A method of preventing exploitation of a vulnerability of a computing system includes generating a deprivation token to cause disabling of a selected one or more features of a component of the computing system to prevent an exploit of a vulnerability affecting the selected one or more features; and publishing the derivation token to at least one of a computing system manufacturer computing system and an enterprise information technology (IT) computing system for distribution to affected computing systems.

Threat prevention by selective feature deprivation

A system and method of detecting and remediating attacks includes receiving operating system (OS) read/write data from an OS, the OS read/write data describing at least one of reads from and writes to a storage device over a file system interface of the OS; collecting storage device read/write data, the storage device read/write data describing at least one of reads from and writes to the storage device; comparing the OS read/write data to the storage device read/write data; and determining if there is a discrepancy between the OS read/write data and the storage device read/write data. If there is a discrepancy, determining if there is an anomaly detected between OS read/write data and the storage device read/write data. If there is an anomaly, causing a remediation action to be taken to stop a malware attack.

Ransomware detection and remediation

Growing community of inventors

Rishon Le-Tzion, Israel

Omer Ben-Shalom