Anup K. Ghosh - Centreville VA, US Sushil Jajodia - Oakton VA, US Yih Huang - Fairfax VA, US Jiang Wang - Fairfax VA, US
International Classification:
G06F 9/455
US Classification:
718 1
Abstract:
An on-demand disposable virtual work system that includes: a virtual machine monitor to host virtual machines, a virtual machine pool manager, a host operating system, a host program permissions list, and a request handler module. The virtual machine pool manager manages virtual machine resources. The host operating system interfaces with a user and virtual machines created with an image of a reference operating system. The host program permissions list may be a black list and/or a white list used to indicate allowable programs. The request handler module allows execution of the program if the program is allowable. If the program is not allowable, the host request handler module: denies program execution and urges a virtual machine specified by the virtual machine pool manager to execute the program. The virtual machine is terminated when the program closes.
Distributed Sensor For Detecting Malicious Software
Anup Ghosh - Centreville VA, US Yih Huang - Fairfax VA, US Jiang Wang - Fairfax VA, US Angelos Stavrou - Springfield VA, US
International Classification:
G06F 11/00
US Classification:
726 23
Abstract:
Processor(s) for detecting malicious software. A hardware virtual machine monitor (HVMM) operates under a host OS. Container(s) initialized with network application template(s)operate under a guest OS VM. A detection module operates under the guest OS VM includes a trigger detection module, a logging module and a container command module. The trigger detection module monitors activity on container(s) for a trigger event. The logging module writes activity report(s) in response to trigger event(s). The container command module issues command(s) in response to trigger event(s). The command(s) include a container start, stop and revert commands. A virtual machine control console operates under the host OS and starts/stops the HVMM. A container control module operates under the guest OSVM and controls container(s) in response to the command(s). The server communication module sends activity report(s) to a central collection network appliance that maintains a repository of activities for infected devices.
Anup K. Ghosh - Centreville VA, US Sushil Jajodia - Oakton VA, US Yih Huang - Fairfax VA, US Jiang Wang - Fairfax VA, US
International Classification:
G06F 21/00 G06F 3/048 G06F 15/16
US Classification:
726 23, 715733
Abstract:
An embodiment for providing a secure virtual browsing environment includes creating a virtual browsing environment with a virtualized operating system sharing an operating system kernel of a supporting operating system and executing the browser application within the virtual browsing environment. Another embodiment includes receiving a website selection within a browser application, determining if the website selection corresponds to a secure bookmark, and creating a second virtual browsing environment and executing the browser application within the second virtual browsing environment to access the website selection when the website selection corresponds to a website specified as a secure bookmark. Yet another embodiment includes monitoring operation of the operating system within the at least one virtual browsing environment, determining when the operation of the operating system includes potential malicious activity, and terminating the virtual browsing environment when the operation includes potential malicious activity.
Anup K. Ghosh - Centreville VA, US Kun Sun - Fairfax VA, US Jiang Wang - Fairfax VA, US Angelos Stavrou - Springfield VA, US
International Classification:
G06F 15/173
US Classification:
709224
Abstract:
A hardware-assisted integrity monitor may include one or more target machines and/or monitor machines. A target machine may include one or more processors, which may include one or more system management modes (SMM). A SMM may include one or more register checking modules, which may be configured to determine one or more current CPU register states. A SMM may include one or more acquiring modules, which may be configured to determine one or more current memory states. A SMM may include one or more network modules, which may be configured to direct one or more communications, for example of one or more current CPU register states and/or current memory states, to a monitor machine. A monitor machine may include one or more network modules and/or analysis modules. An analysis module may be configured to determine memory state differences and/or determine CPU register states differences.
Anup K. Ghosh - Centerville VA, US Kun Sun - Fairfax VA, US Jiang Wang - Fairfax VA, US Angelos Stavrou - Springfield VA, US
International Classification:
G06F 15/177
US Classification:
713 2
Abstract:
An interoperable firmware memory containing a Basic Input Output System (BIOS) and a trusted platform module (TPSM). The BIOS includes CPU System Management Mode (SMM) firmware configured as read-only at boot. The SMM firmware configured to control switching subsequent to boot between at least: a first memory and second isolated memory; and a first and second isolated non-volatile storage device. The first memory including a first operating system and the second memory including a second operating system. The first non-volatile storage device configured to be used by the first operating system and the second non-volatile storage device configured to be used by the second operating system. The trusted platform module (TPSM) configured to check the integrity of the CPU system Management Mode (SMM) during the boot process.
- Mountain View CA, US Xiaojie Jin - Palo Alto CA, US Joshua Foster Slocum - San Francisco CA, US Shengyang Dai - Mountain View CA, US Jiang Wang - Mountain View CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06N 3/04 G06N 20/00 G06F 16/901
Abstract:
Methods, and systems, including computer programs encoded on computer storage media for neural network architecture search. A method includes defining a neural network computational cell, the computational cell including a directed graph of nodes representing respective neural network latent representations and edges representing respective operations that transform a respective neural network latent representation; replacing each operation that transforms a respective neural network latent representation with a respective linear combination of candidate operations, where each candidate operation in a respective linear combination has a respective mixing weight that is parameterized by one or more computational cell hyper parameters; iteratively adjusting values of the computational cell hyper parameters and weights to optimize a validation loss function subject to computational resource constraints; and generating a neural network for performing a machine learning task using the defined computational cell and the adjusted values of the computational cell hyper parameters and weights.
- Mountain View CA, US Jiang Wang - Santa Clara CA, US Shengyang Dai - Dublin CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06Q 30/04 G06V 30/412 G06V 30/414
Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for converting unstructured documents to structured key-value pairs. In one aspect, a method includes: providing an image of a document to a detection model, wherein: the detection model is configured to process the image to generate an output that defines one or more bounding boxes generated for the image; and each bounding box generated for the image is predicted to enclose a key-value pair including key textual data and value textual data, wherein the key textual data defines a label that characterizes the value textual data; and for each of the one or more bounding boxes generated for the image: identifying textual data enclosed by the bounding box using an optical character recognition technique; and determining whether the textual data enclosed by the bounding box defines a key-value pair.
Systems And Methods For Object Detection Using Image Tiling
Jilin TU - Mountain View CA, US Jiang WANG - Mountain View CA, US Huizhong CHEN - Mountain View CA, US Xiangxin ZHU - Mountain View CA, US Shengyang DAI - Mountain View CA, US - Mountain View CA, US
International Classification:
G06V 10/50 G06V 10/778 G06V 10/75
Abstract:
A computing system for detecting objects in an image can perform operations including generating an image pyramid that includes a first level corresponding with the image at a first resolution and a second level corresponding with the image at a second resolution. The operations can include tiling the first level and the second level by dividing the first level into a first plurality of tiles and the second level into a second plurality of tiles; inputting the first plurality of tiles and the second plurality of tiles into a machine-learned object detection model; receiving, as an output of the machine-learned object detection model, object detection data that includes bounding boxes respectively defined with respect to individual ones of the first plurality of tiles and the second plurality of tiles; and generating image object detection output by mapping the object detection data onto an image space of the image.
Starvista
It Assistant
Arey Jones Educational Solutions Nov 2015 - Dec 2016
Pc Integration Technician
Mariposahill.com Feb 2013 - Jul 2015
Administrative Assistant
Education:
College of San Mateo 2012 - 2013
San Francisco State University 2005 - 2010
Bachelors, Bachelor of Science, Accounting, International Business
Skills:
Chinese Netsuite Quickbooks Zoovy Amazon Photoshop Microsoft Office Office 365 Customer Service Windows 7 Windows 10 Solid State Drive Technical Support Phone Etiquette Technical Writing English Logmein Remote Desktop Laptops Printer Support Dell Computers Information Technology
Languages:
English Mandarin
Certifications:
Comptia A Ce Comptia Rackspace, the #1 Managed Cloud Company, License 75D698Df-55C8-4D49-A8D4-D84Fe3... Linuxacademy.com Comptia A+ License 75D698Df-55C8-4D49-A8D4-D84Fe3... Introduction To the Linux Academy Linux Essentials Certification Comptia Cloud Essentials Certification Aws Concepts Cloudu Comptia Project+ Jamf Certified Associate Itil 4 Foundation Nucamp Certificate of Completion Nucamp Coding Bootcamp - Html, Css, Javascript
Apple
Senior Software Engineer - Motion Sensing
Intelinair Jan 2015 - Dec 2015
Senior Engineer
Electron International Ii Nov 2012 - Dec 2014
Senior System Engineer
Zona Technology Mar 2009 - Nov 2012
R and D Control Engineer
Virginia Tech Aug 2004 - Dec 2008
Graduate Research Assistant
Education:
Virginia Tech 2004 - 2009
Doctorates, Doctor of Philosophy, Engineering, Philosophy
Old Dominion University 2002 - 2004
Masters, Engineering
Beihang University 1996 - 2001
Bachelors, Bachelor of Science, Engineering
Skills:
Simulations Simulink Matlab C Aircraft Control Systems Design System Identification Fortran Control Theory Flight Simulation Aeroelasticity Modeling Mathematical Modeling Latex Embedded Systems Aerospace Engineering Flight Mechanics Adaptive Control Robust Control C++ Flight Control Grant Writing Aeroservoelasticity Flight Test Data Analysis Stateflow Model Arp 4754 Arp 4761 Do 178 Misra Rtos Linux Ins/Gps Doors Aerospace Algorithms Testing Avionics R&D Engineering Software Development Integration Drone Systems Engineering Machine Learning Python Optimization Data Analysis Sensor Fusion System Integration Testing Drones Project Management