Abstract: A 3D device includes a first semiconductor chip and a second semiconductor chip stacked vertically. The first semiconductor chip includes a first plurality of tiles. The second semiconductor chip includes a second plurality of tiles. A bus electrically couples each of the first plurality of tiles to a corresponding one of the second plurality of tiles based on assignments of the first plurality of tiles and the second plurality of tiles to tile-to-tile pairs that define a minimized sum of bus delays among each possible tile-to-tile pairs. In each tile-to-tile pair, a net electrically couples each of a first plurality of pins to a corresponding one of a second plurality of pins based on assignments of the first plurality of pins to the second plurality of pins that define a minimized sum of net delays among each possible pin-to-pin pairs.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to analyze telemetry data of a network device for malicious activity. An example apparatus includes an interface to obtain first telemetry data, a rules generator to, using the first telemetry data, generate a global block list using a machine learning model, the machine learning model generated based on a device specific block list and a device specific allow list, and a model manager to transmit the global block list to a gateway, the gateway to facilitate on-path classification of second telemetry data.

Abstract: There is disclosed a computer-implemented system and method of detecting a device that deceptively misidentifies itself on a home network, including sending, to the device, discovery probes, and receiving in response to the discovery probes a self-reported identity; performing a verification of the self-reported identity, comprising over a time greater than one hour, monitoring network traffic from the device to determine whether network traffic over the time is consistent with expected network traffic for the self-reported identity; and upon determining that the network traffic is not consistent, designating the device as potentially deceptively misidentified, and acting to mitigate the device's activity.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to build privacy preserving models. An example apparatus disclosed herein includes processor circuitry to initialize a local model with tokenized parameters associated with server telemetry data, the tokenized parameters included in a first modeling plan retrieved from a server, cause the local model to train based on trigger parameters from the first modeling plan, the local model to train with (a) the tokenized parameters associated with the server telemetry data and (b) client telemetry data, calculate an accuracy metric of the local model based on client-side ground truth data, and label the local model as one of valid or invalid based on a comparison between the accuracy metric and an accuracy threshold.

Abstract: There is disclosed in one example a computing apparatus, including: a hardware platform including a processor and a memory; a network interface to communicatively couple to a network; and a network gateway engine to identify devices on the network, the network gateway engine including instructions encoded within the memory to instruct the processor to provide two-phase identification for a device newly-identified on the network, including: a static identification phase including applying discovery probes to the newly-identified device; and a dynamic identification phase including collecting network telemetry for the newly-identified device over time and analyzing the collected network telemetry to determine if the network telemetry is consistent with expected network usage for the newly-discovered device.

Abstract: A method renders photorealistic images in a web browser. The method is performed at a computing device having a general purpose processor and a graphics processing unit (GPU). The method includes obtaining an environment map and images of an input scene. The method also includes computing textures for the input scene including by encoding an acceleration structure of the input scene. The method further includes transmitting the textures to shaders executing on a GPU. The method includes generating samples of the input scene, by performing at least one path tracing algorithm on the GPU, according to the textures. The method also includes lighting or illuminating a sample of the input scene using the environment map, to obtain a lighted scene, and tone mapping the lighted scene. The method includes drawing output on a canvas, in the web browser, based on the tone-mapped scene to render the input scene.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to build privacy preserving models. An example apparatus disclosed herein includes a training manager to generate a first modeling plan for client-side resources, and transmit the first modeling plan to the client-side resources. The example apparatus also includes a data aggregator to search for a primary validation flag in response to retrieving client-side model parameters, and an accuracy calculator to, in response to detecting the primary validation flag, perform a secondary validation corresponding to the client-side model parameters using a server-side ground truth data set, and determine whether to update the global model with the client-side model parameters based on a comparison of results of the secondary validation and a validation threshold.

Abstract: By way of example, a method includes, responsive to a user request to download, from the internet, a downloadable file with executable content, downloading a portion of the downloadable file, wherein the downloadable file is not executable with the portion; after download the portion of the downloadable file, scanning the portion of the downloadable file for malware characteristics to classify the downloadable file; and completing downloading the downloadable file only after determining, based on the scanning of the portion of the downloadable file, that the downloadable file is not malware.

Abstract: A method renders photorealistic images in a web browser. The method is performed at a computing device having a general purpose processor and a graphics processing unit (GPU). The method includes obtaining an environment map and images of an input scene. The method also includes computing textures for the input scene including by encoding an acceleration structure of the input scene. The method further includes transmitting the textures to shaders executing on a GPU. The method includes generating samples of the input scene, by performing at least one path tracing algorithm on the GPU, according to the textures. The method also includes lighting or illuminating a sample of the input scene using the environment map, to obtain a lighted scene, and tone mapping the lighted scene. The method includes drawing output on a canvas, in the web browser, based on the tone-mapped scene to render the input scene.

Abstract: There is disclosed in one example a hardware computing platform, including: a processor; a memory; a network interface; and a security module, including instructions to cause the processor to: receive a request to download a file via the network interface; download a first portion of the file into a buffer of the memory; analyze the first portion for malware characteristics; assign a security classification to the file according to the analysis of the first portion; and act on the security classification.

Abstract: Various implementations described herein are directed to a device with a reset tree having leaf buffers that provide sensed output signals based on a reset-synchronizing input signal. The device may have a first sensor that receives the sensed output signals from the leaf buffers of the reset tree and provides an attack detection signal based on sensing a malicious attack. The device may have a second sensor that receives the reset-synchronizing input signal, receives the attack detection signal from the first sensor and provides a reset alarm signal based on duration of a timing glitch associated with comparing a difference between the reset-synchronizing input signal and the attack detection signal.

Abstract: Various implementations described herein are directed to a device with a reset tree having leaf buffers that provide sensed output signals based on a reset-synchronizing input signal. The device may have a first sensor that receives the sensed output signals from the leaf buffers of the reset tree and provides an attack detection signal based on sensing a malicious attack. The device may have a second sensor that receives the reset-synchronizing input signal, receives the attack detection signal from the first sensor and provides a reset alarm signal based on duration of a timing glitch associated with comparing a difference between the reset-synchronizing input signal and the attack detection signal.

Abstract: A method renders photorealistic images in a web browser. The method is performed at a computing device having a general purpose processor and a graphics processing unit (GPU). The method includes obtaining an environment map and images of an input scene. The method also includes computing textures for the input scene including by encoding an acceleration structure of the input scene. The method further includes transmitting the textures to shaders executing on a GPU. The method includes generating samples of the input scene, by performing at least one path tracing algorithm on the GPU, according to the textures. The method also includes lighting or illuminating a sample of the input scene using the environment map, to obtain a lighted scene, and tone mapping the lighted scene. The method includes drawing output on a canvas, in the web browser, based on the tone-mapped scene to render the input scene.

Abstract: A method renders photorealistic images in a web browser. The method is performed at a computing device having a general purpose processor and a graphics processing unit (GPU). The method includes obtaining an environment map and images of an input scene. The method also includes computing textures for the input scene including by encoding an acceleration structure of the input scene. The method further includes transmitting the textures to shaders executing on a GPU. The method includes generating samples of the input scene, by performing at least one path tracing algorithm on the GPU, according to the textures. The method also includes lighting or illuminating a sample of the input scene using the environment map, to obtain a lighted scene, and tone mapping the lighted scene. The method includes drawing output on a canvas, in the web browser, based on the tone-mapped scene to render the input scene.

Abstract: There is disclosed in one example a hardware computing platform, including: a processor; a memory; a network interface; and a security module, including instructions to cause the processor to: receive a request to download a file via the network interface; download a first portion of the file into a buffer of the memory; analyze the first portion for malware characteristics; assign a security classification to the file according to the analysis of the first portion; and act on the security classification.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to build privacy preserving models. An example apparatus disclosed herein includes a training manager to generate a first modeling plan for client-side resources, and transmit the first modeling plan to the client-side resources. The example apparatus also includes a data aggregator to search for a primary validation flag in response to retrieving client-side model parameters, and an accuracy calculator to, in response to detecting the primary validation flag, perform a secondary validation corresponding to the client-side model parameters using a server-side ground truth data set, and determine whether to update the global model with the client-side model parameters based on a comparison of results of the secondary validation and a validation threshold.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to analyze telemetry data of a network device for malicious activity. An example apparatus includes an interface to obtain first telemetry data, a rules generator to, using the first telemetry data, generate a global block list using a machine learning model, the machine learning model generated based on a device specific block list and a device specific allow list, and a model manager to transmit the global block list to a gateway, the gateway to facilitate on-path classification of second telemetry data.

Abstract: There is disclosed in one example a computing apparatus, including: a hardware platform including a processor and a memory; a network interface to communicatively couple to a network; and a network gateway engine to identify devices on the network, the network gateway engine including instructions encoded within the memory to instruct the processor to provide two-phase identification for a device newly-identified on the network, including: a static identification phase including applying discovery probes to the newly-identified device; and a dynamic identification phase including collecting network telemetry for the newly-identified device over time and analyzing the collected network telemetry to determine if the network telemetry is consistent with expected network usage for the newly-discovered device.

Abstract: A method renders photorealistic images in a web browser. The method is performed at a computing device having a general purpose processor and a graphics processing unit (GPU). The method includes obtaining an environment map and images of an input scene. The method also includes computing textures for the input scene including by encoding an acceleration structure of the input scene. The method further includes transmitting the textures to shaders executing on a GPU. The method includes generating samples of the input scene, by performing at least one path tracing algorithm on the GPU, according to the textures. The method also includes lighting or illuminating a sample of the input scene using the environment map, to obtain a lighted scene, and tone mapping the lighted scene. The method includes drawing output on a canvas, in the web browser, based on the tone-mapped scene to render the input scene.

Abstract: Mechanisms (which can include systems, methods, and media) for securing an Internet of Things (IoT) device are provided, the mechanisms comprising: receiving a DNS request identifying a fully qualified domain name (FQDN) that originated from the IoT device; in response to receiving the DNS request, determining by a hardware processor whether to allow or drop a connection between the IoT device and a target domain corresponding to the FQDN; and responding to the DNS request with instructions to allow or drop the connection based on the determining.