Abstract: An electronic device includes a communication interface and at least one processor configured for: transmitting to or receiving from a second electronic device over proximity-based communication channel an introduction message including a first encryption key; receiving, from a server via the at least one communication interface, a challenge notification providing notification of a challenge to be completed to initiate a data process, the challenge notification including or providing access to at least one data field associated with a verification challenge; identifying, from the at least one data field, an encrypted challenge response value; decrypting the encrypted challenge response value with a key corresponding to the first encryption key; and transmitting the decrypted challenge response value to the server to complete the challenge to initiate the data process.

Abstract: A memory device configured as a dynamic random access memory is provided, comprising a first semiconductor device layer comprising a first bit cell and a second semiconductor device layer comprising a second DRAM bit cell. Further, at least one of a first and second interconnecting structure is provided, the first interconnecting structure extending vertically between the first and second semiconductor device layer and being arranged to form a write word line common to the gate terminal of the write transistors of the first and second bit cells, and the second interconnecting structure extending vertically between the first and second semiconductor device layer and being arranged to form a read word line common to a first source/drain terminal of the read transistors of the first and second bit cells.

Abstract: Features are disclosed for correlating a workload type with particular volume characteristics for a block storage volume. The volume characteristics may include a durability or a performance consistency for a particular volume. A computing device can obtain a set of workload parameters indicating a workload associated with a particular block storage volume. Based on the set of workload parameters, the computing device can determine a workload classification that links the set of workload parameters to a set of volume characteristics. The computing device can further compare the set of volume characteristics with the current set of volume characteristics for the block storage volume. Based on comparing the sets of volume characteristics, the computing device may determine a recommendation for a user. The computing device can dynamically modify the block storage volume based on the recommendation.

Abstract: Techniques unmasking ransomware attacks are disclosed. In some embodiments, a computer system performs operations comprising: generating a first prediction that a file system comprising a plurality of files has been attacked by ransomware based on snapshot metadata of the file system using a snapshot-level machine learning prediction model, the snapshot metadata comprising a plurality of file change data indicating a plurality of file change events that have been performed on the file system; in response to the first prediction, generating a classification for each one of the files based on the file change data using a file-level machine learning prediction model, the classification indicating whether the files have been targeted by the ransomware for encryption; determining that one or more files have been targeted by the ransomware based on the classification; and displaying the classification for the one or more files on a computing device of a user.

Abstract: Techniques for implementing a scalable automated training framework for anomaly and ransomware detection are disclosed. In some embodiments, a computer system performs operations comprising: instantiating a plurality of virtual machines, each one of the virtual machines being loaded with a corresponding file system; simulating user actions and ransomware on the virtual machines, the simulating of user actions and ransomware on the virtual machines causing changes to the corresponding file systems of the virtual machines; for each one of the plurality of virtual machines, generating a corresponding metadata file based on one or more corresponding snapshots of the virtual machine, the one or more corresponding snapshots indicating the changes to the corresponding file system of the virtual machine; and training a ransomware detection model using a machine learning algorithm and training data, the training data being based on the corresponding metadata files of the virtual machines.

Abstract: In accordance with some embodiments, systems, methods, and media for improving signal-to-noise ratio in single-photon data are provided. In some embodiments, a system comprises: a processor programmed to: generate, for each of a plurality of pixel locations, initial photon flux estimates based on a first set of photon transients including photon transients associated with the pixel location and neighboring pixel locations, each of the photon transients comprises a histogram of photon counts; identify, for a scene patch associated with each of the plurality of pixel locations, one or more similar scene patches using intensity information for each of the plurality of pixel locations; and generate, for each of the plurality of pixel locations, final photon flux estimates based on a second set of photon transients including photon transients associated with the scene patch and each of the one or more similar scene patches.

Abstract: A system and method of receiving a voice command while a user is moving in an Internet of Things (IoT) environment comprising a plurality of virtual assistants (VAs) is provided. The method includes receiving a first audio uttered by a user at a first VA. The user's intention to speak more (ISM) is determined based on the user's breathing pattern. Furthermore, the method includes selecting a second VA to initiate listening to a second audio uttered by the user, based on detecting a movement of the user with respect to the plurality of VAs in the IoT environment. The method includes merging the first audio and the second audio to determine a voice command corresponding to the user's complete utterance, for execution within the IoT environment.

Abstract: An Internet-connected device, such as a car, refrigerator, or even a laptop can use a second device, such as a cell phone, to support cryptographic operations and communication with token service providers or other processing services requiring pre-provisioned capabilities that may include cryptographic secrets. By removing the need to store personally sensitive data in “Internet of Things” (IoT) devices, a user's personal information and other sensitive financial information may be contained to a relatively small number of devices. This may help prevent theft of goods or services by IoT devices that are not always under the close control of the user.

Abstract: The disclosed technology relates to a non-volatile (NV) static random-access memory (SRAM) device, and to a method of operating the same. The NV-SRAM device includes a plurality of bit-cells, wherein each bit-cell comprises: an SRAM bit-cell; a first bit-line connected via a first access element to the SRAM bit-cell; a NV bit-cell connected via a switch to the SRAM bit-cell; and a second bit-line connected via a second access element to the NV bit-cell. The NV-SRAM device is configured to independently write data from the first bit-line into the SRAM bit-cell through the first access element, and respectively from the second bit-line into the NV bit-cell through the second access element.

Abstract: A client device, such as a mobile phone or a mobile phone accessory (e.g., phone case), is provided that receives and transmits data (e.g., a social media code) via light wave communication. The light wave communication may comprise structured light (e.g., projected light patterns). The client device may include a lightbox comprised of LEDs located on a back face of the client device.

Abstract: Techniques are provided for providing a storage abstraction layer for a composite aggregate architecture. A storage abstraction layer is utilized as an indirection layer between a file system and a storage environment. The storage abstraction layer obtains characteristic of a plurality of storage providers that provide access to heterogeneous types of storage of the storage environment (e.g., solid state storage, high availability storage, object storage, hard disk drive storage, etc.). The storage abstraction layer generates storage bins to manage storage of each storage provider. The storage abstraction layer generates a storage aggregate from the heterogeneous types of storage as a single storage container. The storage aggregate is exposed to the file system as the single storage container that abstracts away from the file system the management and physical storage details of data of the storage aggregate.

Abstract: Methods for assessing genomic instability (GI) may include selectively amplifying nucleic acid sequences at targeted locations in a tumor sample genome by a targeted panel with a low sample input to generate a plurality of nucleic acid sequence reads; dividing the genome into segments having homogeneous copy numbers using log odds of heterozygous SNPs and CNV log ratios determined for the nucleic acid sequence reads; applying a threshold count to squared allelic log odds of each segment in autosomes of the genome to identify unbalanced copy number (UCN) segments; adding numbers of bases in the UCN segments to produce a sum of UCN bases; and dividing the sum of UCN bases by the total number of bases in all the segments identified in the autosomes of the sample genome to produce a ratio indicative of genomic instability. The ratio may be expressed as a percent to give a GI score.

Abstract: In accordance with some embodiments, systems, methods, and media for estimating depths in a scene using single-photon detectors and binary structured light patterns are provided. In some embodiments, a system comprises: a light source; an image sensor comprising an array including single-photon detectors; a processor programmed to: cause the light source to emit a sequence of n binary light patterns toward the scene, each comprising at least L columns, each of the patterns has a minimum stripe width of 8 columns; and n>log2(L); cause, for each of the n binary light patterns, the image sensor to capture a binary image of the scene, the binary image comprises a binary value for each of single-photon detectors such that each of the single-photon detectors generates a set of binary values; and estimate, for each single-photon detector, a depth value based on the set of binary values.

Abstract: A device may include a Josephson junction between at least three terminals. The device is configured to exhibit a superconducting diode effect. A method may include forming a Josephson layer including three terminals defining a Josephson junction. The method may further include forming, over the Josephson layer, a gate layer including at least three gates. Each gate of the at least three gates extends across a respective channel between a respective terminal pair of the three terminals. The Josephson layer and gate layer are configured to exhibit a superconducting diode effect.

Abstract: According to an aspect there is provided a memory cell. The memory cell comprises: a first and a second electrode; a spin-orbit-torque, SOT, layer comprising a first and a second electrode contact portion arranged in contact with the first and the second electrode, respectively, and an intermediate portion between the first and second electrode contact portions; a first magnetic tunnel junction, MTJ, layer stack arranged in contact with the intermediate portion; and a second MTJ layer stack arranged in contact with the second electrode contact portion and directly above the second electrode. A memory device comprising such a memory cell and a method for writing to such a memory cell are also provided.

Abstract: In accordance with some embodiments, systems, methods, and media for single photon depth imaging with improved efficiency using compressive histograms are provided. In some embodiments, the system comprises: a light source; a detector configured to detect arrival of individual photons; a processor programmed to: detect a photon arrival; determine a time bin i of the photon arrival in a range from 1 to N a total number of time bins; update a compressed histogram comprising K stored values representing bins of the compressed histogram based on K values in a code word represented by an ith column of a coding matrix C having dimension K×N, with each column different than each other column, and each column corresponds to a single time bin i; and estimate a depth value based on the K values.

Abstract: The material layer stack includes first and second magnetic tunnel junctions and a first top electrode formed on a top face of the stack. A shoulder is formed on a lateral face of the stack and divides the stack into a lower portion and an upper portion. A tunnel barrier of the first magnetic tunnel junction is comprised by the lower stack portion and a tunnel barrier of the second magnetic tunnel junction by the upper stack portion. A second top electrode is formed on the shoulder. Each magnetic tunnel junction is adapted to store a bit as a reconfigurable magnetoresistance of its magnetic electrodes. Preferably, a bottom face of the stack is connected to a conductor supporting current induced magnetic polarization switching for the first magnetic tunnel junction by spin-orbit torque. Magnetic polarization switching for the second magnetic tunnel junction is preferably achieved by spin-transfer torque.

Abstract: In accordance with some embodiments, systems, methods, and media for generating and using neural networks having improved efficiency for analyzing video are provided. In some embodiments, the method comprises: providing image data to a trained neural network; receiving, at a neuron, a delta-based input ?in from a previous layer; generating an output g(?in) of a linear transform g; generating an updated state variable a based on g(?in) and a current a; generating an output f(a) of an activation function f based on updated a; generating an updated state variable d based on a current d, a state variable b, and f(a); generating an updated b based on output f(a); transmitting d to a next layer based on a transmission policy and subtracting the value from d; and receiving an output from the trained neural network that represents a prediction based on the image data.

Abstract: Techniques for implementing proactive data security operations for files using an analysis of access permission levels for the files are disclosed. In some embodiments, a computer system performs operations comprising: determining that data of a file includes sensitive information based on an analysis of the data using a data classification model; determining that access to the file is open using an access classification model; and based on the determination that the data of the file includes sensitive information and the determination that the access to the file is open, causing a notification to be displayed on a computing device of a user, the notification comprising an indication that the file includes sensitive information and that access to the file is open.

Abstract: An accelerator circuit is provided that includes an inverter chain having an input coupled to a data line and a sense circuit having inputs coupled to an output of the inverter chain and the data line. The sense circuit is configured to sense a rise toward a supply voltage on the data line or a fall toward a ground voltage on the data line. The accelerator circuit further includes an amplify circuit having inputs coupled to outputs of the sense circuit and an output coupled to the data line, where the amplify circuit is configured to amplify the data line toward the supply voltage or toward the ground voltage based on amplify enable signals output by the sense circuit.