Abstract: A cloud-based network security system (NSS) is described. The NSS extracts information about a document (e.g., a portable document format (PDF) file) and uses heuristic rules to analyze the information to predict whether the document contains malicious software. Specifically, prior to detonation of the document, object features, code features, and embedded features of the document are extracted. The extracted information is input to a classification engine that applies sets of heuristic rules to groups of the features of the document to provide an output indicating a prediction of whether the document contains malware. A routing engine provides the document for further analysis (e.g., deep scanning) if the document is suspicious or bypasses the further analysis if the document is benign. Security policies can then be applied based on the classification.

Abstract: A solid precursor heating device for induction heating includes a stainless steel cylinder and a plurality of vertically stacked trays. The stainless steel cylinder has a bottom plate, a peripheral wall, a cover, and a vapor output pipe. The bottom plate and the peripheral wall define an interior space. The cover is provided on a top portion of the peripheral wall in a separable manner. The vapor output pipe is provided at the cover and is in communication with the interior space. The magnetic permeability of the stainless steel cylinder is higher than 1 H/m. The trays are provided in the interior space in a separable manner, and each tray has an accommodating space, a supporting plate, an annular side, and a circular ring, with the accommodating space defined between the supporting plate, the annular side, and the circular ring.

Abstract: A pressure-controlled solid precursor heating device includes a steel cylinder, a plurality of trays, a buffering container, a pressure gage, and an induction heater. The steel cylinder has a bottom plate and a peripheral wall, the two of which define an interior space. The trays are vertically stacked in the interior space in a separable manner and each have an accommodating space, a supporting plate, an annular side, and a circular ring, with the accommodating space defined between the supporting plate, the annular side, and the circular ring. The buffering container has a buffering space fluidly connected to the interior space. The pressure gage is provided at the buffering container and senses the vapor pressure in the buffering space. The induction heater is in signal connection with the pressure gage and heats the steel cylinder, by induction heating, according to the vapor pressure sensed by the pressure gage.

Abstract: An estimation method for buried pipeline depth is provided, which includes the following steps. Current seawater temperature measurement data is obtained. Current seabed temperature simulation data is generated according to the current seawater temperature measurement data using an ambient temperature estimation model. Current cable temperature simulation data is generated according to the current seabed temperature simulation data using a thermal fluid-solid coupling model. Current cable temperature measurement data is obtained. A current buried pipeline depth estimation result is generated according to the current cable temperature simulation data and the current cable temperature measurement data using a buried pipeline depth estimation model.

Abstract: A waveguide plate for conducting ultrasonic signal between a high temperature pipeline and an ultrasonic transducer. The waveguide plate comprises a plate part and multiple periodic holes. The multiple periodic holes penetrate the plate part in a direction perpendicular to the plate part. The waveguide plate with the multiple periodic holes can achieve enhanced heat insulation and ultrasonic conduction efficiency while decreasing size per se.

Abstract: A cloud-based network security system (NSS) is described. The NSS uses a sandbox to safely open and extract information about a PDF file and uses machine learning algorithms to analyze the information to predict whether the PDF file contains malware. Specifically, dynamic information about the PDF file is captured while it is open in the sandbox. Static information is extracted from the PDF file as well. The dynamic and static information is input to an AI or machine learning model trained to provide an output indicating a prediction of whether the PDF file contains malware. A verdict engine uses the output from the AI or machine learning model to classify the document as malicious or clean. Security policies can then be applied based on the classification.

Abstract: A cloud-based network security system (NSS) is described. The NSS uses a sandbox to safely open and extract information about a PDF file and uses machine learning algorithms to analyze the information to predict whether the PDF file contains malware. Specifically, dynamic information about the PDF file is captured while it is open in the sandbox. Static information is extracted from the PDF file as well. The dynamic and static information is input to an AI or machine learning model trained to provide an output indicating a prediction of whether the PDF file contains malware. A verdict engine uses the output from the AI or machine learning model to classify the document as malicious or clean. Security policies can then be applied based on the classification.

Abstract: A cloud-based network security system (NSS) is described. The NSS extracts information about a document (e.g., a portable document format (PDF) file) and uses heuristic rules to analyze the information to predict whether the document contains malicious software. Specifically, prior to detonation of the document, object features, code features, and embedded features of the document are extracted. The extracted information is input to a classification engine that applies sets of heuristic rules to groups of the features of the document to provide an output indicating a prediction of whether the document contains malware. A routing engine provides the document for further analysis (e.g., deep scanning) if the document is suspicious or bypasses the further analysis if the document is benign. Security policies can then be applied based on the classification.

Abstract: The present invention relates to a computer virus interception method. The method includes: executing the following steps by a processor unit: providing for a user to configure a default software status list by operating a default status configuration interface, wherein the default software status list includes a plurality of macro application software; providing for the user to configure a software whitelist by operating a software whitelist configuration interface; providing for the user to configure a hardware whitelist by operating a hardware whitelist configuration interface; and performing an identity re-authentication process to re-authenticate an identity information of the user when one of a default status change operation, a software whitelist change operation, a hardware whitelist change operation, and a software whitelist anomaly is detected.

Abstract: The present disclosure describes a device that includes an enclosure, a cover glass coupled to the enclosure to cover a side portion of the enclosure, a light sensor directed to receive light through the cover glass, and a light altering device positioned between the light sensor and the cover glass to collect light from a position blocked by the enclosure.

Abstract: A cloud-based network security system (NSS) is described. The NSS extracts information about a document (e.g., a portable document format (PDF) file) and uses heuristic rules to analyze the information to predict whether the document contains malicious software. Specifically, prior to detonation of the document, object features, code features, and embedded features of the document are extracted. The extracted information is input to a classification engine that applies sets of heuristic rules to groups of the features of the document to provide an output indicating a prediction of whether the document contains malware. A routing engine provides the document for further analysis (e.g., deep scanning) if the document is suspicious or bypasses the further analysis if the document is benign. Security policies can then be applied based on the classification.

Abstract: Analysis of an integrated circuit (IC) includes acquiring a review scanning electron microscope (RSEM) image of the IC, and acquiring a voltage contrast electron beam image of the IC. A layout image is rendered from a layout file descriptive of a layout of the IC. A transform between spatial coordinates of the RSEM image of the IC and spatial coordinates of the voltage contrast electron beam image of the IC is determined using the layout image. A voltage contrast (VC) defect or other VC targeted pattern is identified in the voltage contrast electron beam image of the IC, and at least one region of interest (ROI) is located in the RSEM image of the IC associated with the VC defect using the spatial transform. The at least one ROI in the RSEM image of the IC is analyzed to produce information for the VC defect or other VC targeted pattern.

Abstract: The present invention relates to an authentication information manager computer program product, which is executed by a processing unit. The computer program product includes: a physical private key acquisition module configured to receive an identity information to form an initialization authentication information including a part of the identity information; an authentication information management module configured to record a first set of authentication information for logging into a first networking application; and a multiparty multifactor dynamic strong encryption authentication transmission module configured to implement a multiparty multifactor dynamic digital authentication method with strong encryption to transmit the transfigurated initialization authentication information to a network application serving device including an authentication information manager back end and a third-party security serving equipment to be verified.

Abstract: The present invention relates to a cyber security authentication method for a displayless networking device. The method includes randomly generating an ephemeral decryption key in a displayless networking device application server; providing the ephemeral decryption key and a network address of the displayless networking device to a user device via an optical identifier; initiating a multi-party multi-factor dynamic strong encryption authentication scheme in the user device based on the ephemeral decryption key and the network address to obtain an ephemeral credential; and authenticating an identity information based on the ephemeral decryption key and the ephemeral credential at least by the user device, the displayless networking device application server, and a security server.

Abstract: A cloud-based network security system (NSS) is described. The NSS uses a sandbox to safely detonate and extract information about a document and uses machine learning algorithms to analyze the information to predict whether the document contains malicious software. Specifically, during the detonation, static and dynamic information about the document is captured in the sandbox as well as character strings from images in the document. The dynamic information (and sometimes the static information) is input to an AI or machine learning model trained to provide an output indicating a prediction of whether the document contains malware. The character strings are compared with a batch of phishing keywords to generate a heuristic score. A validation engine combines the output from the AI or machine learning model and the heuristic score to classify the document as malicious or clean. Security policies can then be applied based on the classification.

Abstract: A semiconductor device comprises a fin structure disposed over a substrate; a gate structure disposed over part of the fin structure; a source/drain structure, which includes part of the fin structure not covered by the gate structure; an interlayer dielectric layer formed over the fin structure, the gate structure, and the source/drain structure; a contact hole formed in the interlayer dielectric layer; and a contact material disposed in the contact hole. The fin structure extends in a first direction and includes an upper layer, wherein a part of the upper layer is exposed from an isolation insulating layer. The gate structure extends in a second direction perpendicular to the first direction. The contact material includes a silicon phosphide layer and a metal layer.

Abstract: The present invention relates to a computer virus interception method. The method includes: executing the following steps by a processor unit: providing for a user to configure a default software status list by operating a default status configuration interface, wherein the default software status list includes a plurality of macro application software; providing for the user to configure a software whitelist by operating a software whitelist configuration interface; providing for the user to configure a hardware whitelist by operating a hardware whitelist configuration interface; and performing an identity re-authentication process to re-authenticate an identity information of the user when one of a default status change operation, a software whitelist change operation, a hardware whitelist change operation, and a software whitelist anomaly is detected.

Abstract: A cloud-based network security system (NSS) is described. The NSS uses a sandbox to safely detonate and extract information about a document and uses machine learning algorithms to analyze the information to predict whether the document contains malicious software. Specifically, during the detonation, static and dynamic information about the document is captured in the sandbox as well as character strings from images in the document. The dynamic information (and sometimes the static information) is input to an AI or machine learning model trained to provide an output indicating a prediction of whether the document contains malware. The character strings are compared with a batch of phishing keywords to generate a heuristic score. A validation engine combines the output from the AI or machine learning model and the heuristic score to classify the document as malicious or clean. Security policies can then be applied based on the classification.