Patents by Inventor Sai Zeng

Sai Zeng has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20220129560
    Abstract: Systems and techniques that facilitate automated health-check risk assessment of computing assets are provided. In various embodiments, a system can comprise a baseline component that can generate a baseline health-check risk score that corresponds to non-compliance of a computing asset with a stipulated control. In various aspects, the system can further comprise an adjustment component that can adjust the baseline health-check risk score based on a weakness factor of the stipulated control. In some cases, the weakness factor can be based on a magnitude by which a state of the computing asset deviates from the stipulated control. In various embodiments, the adjustment component can further adjust the baseline health-check risk score based on an environmental factor of the computing asset. In various cases, the environmental factor can be based on security mechanisms or security protocols associated with the computing asset.
    Type: Application
    Filed: October 23, 2020
    Publication date: April 28, 2022
    Inventors: Muhammed Fatih Bulut, Milton H. Hernandez, Robert Filepp, Sai Zeng, Steven Ocepek, Srinivas Babu Tummalapenta, Daniel S. Riley
  • Publication number: 20220122038
    Abstract: An artificial intelligence (AI) platform to support workflow version process control. One or more workflows corresponding to one or more workflow engines are monitored. A neural network is employed to capture a relationship associated with a detected change in the monitored workflows. The neural network is leveraged to identify and assess an impact of the detected change to one or more additional workflows. Responsive to the assessment, the impacted workflow engines are optimized. The optimization includes automatically mapping and encoding changes corresponding to the impacted workflow. The one or more workflows containing the encoded changes are then executed.
    Type: Application
    Filed: October 20, 2020
    Publication date: April 21, 2022
    Applicant: Kyndryl, Inc.
    Inventors: Jun Duan, Qi Ming Teng, Sai Zeng, Christopher Peter Baker, Alexei Karve
  • Publication number: 20220050720
    Abstract: A computer-implemented method for managing one or more operations of a workload includes selecting a resource type for workload management on a platform. One or more operations of the selected resource to be managed are identified. A reconciliation time for execution of each of the identified operations is determined. A reconciliation period between two consecutive reconciliations is determined for each of the identified operations. A minimum number of processes for workload management of a given set of the operations on resources is calculated, and the determined minimum number of processes is deployed to manage the workload.
    Type: Application
    Filed: August 15, 2020
    Publication date: February 17, 2022
    Inventors: Braulio Gabriel Dumba, Ubaid Ullah Hafeez, Abdulhamid Adebayo, Jun Duan, Alexei Karve, Sai Zeng
  • Publication number: 20220050962
    Abstract: Aspects of the present disclosure relate to converting between structured and tabular data formats. Data can be received in a tabular format. An array can be built for each of a plurality of objects within the data in the tabular format, each object corresponding to at least one identified header of the identified headers. A data row can be parsed using at least one of the built arrays and data within the data row can be added to the structured format in a specific location based characteristics indicated in the at least one array. Data can also be converted from the structured format into the tabular format using the built arrays.
    Type: Application
    Filed: August 14, 2020
    Publication date: February 17, 2022
    Inventors: Qi Ming Teng, Christopher Peter Baker, Sai ZENG, Jun Duan
  • Patent number: 11200048
    Abstract: A system, computer program product, and method are provided for supporting risk evaluation and modification of an executable codified infrastructure. The codified infrastructure is analyzed to identify any non-native program instructions. A selection of the identified non-native program instructions are combined and subjected to a risk evaluation by non-native tools. A risk evaluation result is mapped to corresponding lines of the source code, and a risk identifier is assigned to the corresponding lines of the source code. One or more modifications are selectively applied to the codified infrastructure in correspondence with the assigned risk identifier. The applied modification mitigates any defects in the source code.
    Type: Grant
    Filed: May 14, 2020
    Date of Patent: December 14, 2021
    Assignee: International Business Machines Corporation
    Inventors: Alexei Karve, Sai Zeng, Ting Dai
  • Publication number: 20210357206
    Abstract: A system, computer program product, and method are provided for supporting risk evaluation and modification of an executable codified infrastructure. The codified infrastructure is analyzed to identify any non-native program instructions. A selection of the identified non-native program instructions are combined and subjected to a risk evaluation by non-native tools. A risk evaluation result is mapped to corresponding lines of the source code, and a risk identifier is assigned to the corresponding lines of the source code. One or more modifications are selectively applied to the codified infrastructure in correspondence with the assigned risk identifier. The applied modification mitigates any defects in the source code.
    Type: Application
    Filed: May 14, 2020
    Publication date: November 18, 2021
    Applicant: International Business Machines Corporation
    Inventors: Alexei Karve, Sai Zeng, Ting Dai
  • Publication number: 20210334677
    Abstract: A machine learning assessment system is provided. The system identifies multiple datasets and multiple machine learning (ML) modeling algorithms based on the client profile. The system assesses a cost of data collection for each dataset of the multiple datasets. The system assesses a performance metric for each ML modeling algorithm of the multiple modeling algorithms. The system recommends a dataset from the multiple datasets and an ML modeling algorithm from the multiple ML modeling algorithm based on the assessed costs of data collection for the multiple datasets and the assessed performance metrics for the multiple ML modeling algorithms.
    Type: Application
    Filed: April 26, 2020
    Publication date: October 28, 2021
    Inventors: Sai Zeng, Braulio Gabriel Dumba, Jun Duan, Matthew Staffelbach, Emrah Zarifoglu, Umar Mohamed Iyoob, Manish Mahesh Modh
  • Patent number: 11146586
    Abstract: A method and system of identifying a computing device vulnerability is provided. Social media communication is monitored. Social media threads that are related to a vulnerability, based on the monitored social media communication, are identified, filtered, and categorized into one or more predetermined categories of computing device vulnerabilities. Upon determining that a number of social media posts related to the vulnerability is above a first predetermined threshold, one or more dependable social media threads in a same one or more categories as the vulnerability are searched. One or more possible root causes of the vulnerability are determined from the searched dependable social media threads. A validity score for each of the one or more possible root causes is assigned. A possible root cause from that has a highest validity score that is above a second predetermined threshold is selected to be the root cause of the vulnerability.
    Type: Grant
    Filed: January 4, 2020
    Date of Patent: October 12, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Muhammed Fatih Bulut, Lisa Chavez, Jinho Hwang, Anup Kalia, Virginia Mayo Policarpio, Sai Zeng
  • Patent number: 11119751
    Abstract: A self-learning patch-orchestration system receives requests to install instances of two or more types of patches on sets of hardware or software components. The system retrieves information about past efforts to install the same types of patches, including historic failure rates of each type of patch and average durations of time required to successfully install each type of patch. The system identifies a set of candidate patch-orchestration plans, each of which specifies a different sequence in which to install the patches. The system uses the historical records to rank the plans based on the expected loss of scheduled installation time that would be caused by each plan's patch failures. The system selects as optimal the plan incurring the least amount of lost time and other adverse effects, and directs an orchestration engine or other downstream mechanisms to install the requested patches in accordance with the optimal orchestration plan.
    Type: Grant
    Filed: July 16, 2019
    Date of Patent: September 14, 2021
    Assignee: International Business Machines Corporation
    Inventors: Jinho Hwang, Laura Murphy, Cindy J. Mullen, Virginia Mayo Policarpio, Sai Zeng
  • Patent number: 11038779
    Abstract: A self-service experience for a change requester is provided. Authorized endpoint changes are identified along with corresponding change types. Resource attributes are identified and corresponding parameters of the resources are changed according to change window requirements. Where the changes comply with business policies, the changes are executed.
    Type: Grant
    Filed: August 2, 2019
    Date of Patent: June 15, 2021
    Assignee: International Business Machines Corporation
    Inventors: Constantin M. Adam, Shang Q. Guo, Brian L. Peterson, John J. Rofrano, Frederick Y. Wu, Sai Zeng
  • Publication number: 20210150029
    Abstract: Techniques for dynamic server groups that can be patched together using stream clustering algorithms, and learning components in order to reuse the repeatable patterns using machine learning are provided herein. In one example, in response to a first risk associated with a first server device, a risk assessment component patches a server group to mitigate a vulnerability of the first server device and a second server device, wherein the server group is comprised of the first server device and the second server device. Additionally, a monitoring component monitors data associated with a second risk to the server group to mitigate the second risk to the server group.
    Type: Application
    Filed: December 28, 2020
    Publication date: May 20, 2021
    Inventors: Muhammed Fatih Bulut, Jinho Hwang, Vugranam C. Sreedhar, Sai Zeng
  • Publication number: 20210120041
    Abstract: An assessment component that facilitates assessment and enforcement of policies within a computer environment can comprise a compliance component that determines whether a policy, that defines one or more requirements associated with usage of one or more enterprise components of an enterprise computing system, is in compliance with a plurality of standardized policies that govern operation of the one or more enterprise components of the enterprise computing system. The assessment component can also comprise a policy optimization component that determines one or more changes to the policy that achieve the compliance with the plurality of standardized polices based on a determination that the policy complies with a first standardized policy of the plurality of standardized policies and fails to comply with a second standardized policy of the plurality of standardized policies.
    Type: Application
    Filed: December 23, 2020
    Publication date: April 22, 2021
    Inventors: Milton H. Hernandez, Anup Kalia, Brian Peterson, Vugranam C. Sreedhar, Sai Zeng
  • Patent number: 10979456
    Abstract: An assessment component that facilitates assessment and enforcement of policies within a computer environment can comprise a compliance component that determines whether a policy, that defines one or more requirements associated with usage of one or more enterprise components of an enterprise computing system, is in compliance with a plurality of standardized policies that govern operation of the one or more enterprise components of the enterprise computing system. The assessment component can also comprise a policy optimization component that determines one or more changes to the policy that achieve the compliance with the plurality of standardized polices based on a determination that the policy complies with a first standardized policy of the plurality of standardized policies and fails to comply with a second standardized policy of the plurality of standardized policies.
    Type: Grant
    Filed: October 27, 2017
    Date of Patent: April 13, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Milton H. Hernandez, Anup Kalia, Brian Peterson, Vugranam C. Sreedhar, Sai Zeng
  • Patent number: 10977366
    Abstract: Techniques for dynamic server groups that can be patched together using stream clustering algorithms, and learning components in order to reuse the repeatable patterns using machine learning are provided herein. In one example, in response to a first risk associated with a first server device, a risk assessment component patches a server group to mitigate a vulnerability of the first server device and a second server device, wherein the server group is comprised of the first server device and the second server device. Additionally, a monitoring component monitors data associated with a second risk to the server group to mitigate the second risk to the server group.
    Type: Grant
    Filed: December 4, 2019
    Date of Patent: April 13, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Muhammed Fatih Bulut, Jinho Hwang, Vugranam C. Sreedhar, Sai Zeng
  • Patent number: 10938655
    Abstract: Various embodiments collect unproductive resources in a network infrastructure. In one embodiment, data relating to resources of a network infrastructure is collected. An analytics model is selected based on a type of the collected data. The selected analytics model is executed to classify a resource unproductive or productive, and to assign a corresponding confidence level. An action plan for each confidence level is determined and the action plan is executed for the resource. The collected data may include resource utilization information, hypervisor information, cloud related meta-data, user knowledge and system knowledge. When data is only resource data, a resource mining model is selected. When the data includes reference data, a reference mining model is selected. When the data comprises reference data and resource data, a combined mining model is selected.
    Type: Grant
    Filed: January 26, 2016
    Date of Patent: March 2, 2021
    Assignee: International Business Machines Corporation
    Inventors: Karin Murthy, Zhiming Shen, Christopher Charles Young, Sai Zeng
  • Publication number: 20210019135
    Abstract: A self-learning patch-orchestration system receives requests to install instances of two or more types of patches on sets of hardware or software components. The system retrieves information about past efforts to install the same types of patches, including historic failure rates of each type of patch and average durations of time required to successfully install each type of patch. The system identifies a set of candidate patch-orchestration plans, each of which specifies a different sequence in which to install the patches. The system uses the historical records to rank the plans based on the expected loss of scheduled installation time that would be caused by each plan's patch failures. The system selects as optimal the plan incurring the least amount of lost time and other adverse effects, and directs an orchestration engine or other downstream mechanisms to install the requested patches in accordance with the optimal orchestration plan.
    Type: Application
    Filed: July 16, 2019
    Publication date: January 21, 2021
    Inventors: Jinho Hwang, Laura Murphy, Cindy J. Mullen, Virginia Mayo Policarpio, Sai Zeng
  • Patent number: 10873625
    Abstract: Techniques facilitating service management for the infrastructure of blockchain networks are provided. A system comprises a memory and a processor that executes computer executable components stored in the memory. The computer executable components can comprise an allocation component, a grouping component, and an implementation component. The allocation component can assign, within a blockchain network, a first group of nodes of a first node type to a first set of operation slots and a second group of nodes of a second node type, different than the first node type, to a second set of operation slots. The grouping component can aggregate the second group of nodes assigned to the second set of operation slots with the first group of nodes within the first set of operation slots. The implementation component can execute a service management operation. A consensus algorithm can be satisfied during an execution of the service management operation.
    Type: Grant
    Filed: February 26, 2018
    Date of Patent: December 22, 2020
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORA ! ION
    Inventors: Sai Zeng, Jun Duan, Alexei Karve, Neeraj Asthana, Vugranam C. Sreedhar, Nerla Jean-Louis
  • Patent number: 10834183
    Abstract: A method, product, and apparatus for treating idle servers in a cloud system provide for extrapolating a purpose of each of a plurality of servers by comparing a list of processes active on the server to a plurality of lists of processes associated with a plurality of purposes; selecting vectors of idle/active features corresponding to the extrapolated purposes of each of the plurality of servers; classifying as idle or active each of the plurality of servers, by assessing the specified feature vectors using a linear support vector machine; validating as idle or active each server classified as idle, by assessing the connectivity of the server with all servers classified as active; and implementing at least one treatment option on servers that have been validated as idle. The treatment options may include terminating, terminating with snapshot, and stopping a virtual machine.
    Type: Grant
    Filed: December 29, 2017
    Date of Patent: November 10, 2020
    Assignee: International Business Machines Corporation
    Inventors: Jinho Hwang, In Kee Kim, Christopher C. Young, Sai Zeng
  • Patent number: 10834182
    Abstract: A method, product, and apparatus for treating idle servers in a cloud system provide for extrapolating a purpose of each of a plurality of servers by comparing a list of processes active on the server to a plurality of lists of processes associated with a plurality of purposes; selecting vectors of idle/active features corresponding to the extrapolated purposes of each of the plurality of servers; classifying as idle or active each of the plurality of servers, by assessing the specified feature vectors using a linear support vector machine; validating as idle or active each server classified as idle, by assessing the connectivity of the server with all servers classified as active; and implementing at least one treatment option on servers that have been validated as idle. The treatment options may include terminating, terminating with snapshot, and stopping a virtual machine.
    Type: Grant
    Filed: March 29, 2017
    Date of Patent: November 10, 2020
    Assignee: International Business Machines Corporation
    Inventors: Jinho Hwang, In Kee Kim, Christopher C Young, Sai Zeng
  • Patent number: 10778713
    Abstract: A system includes a memory that stores computer executable components and neural network data, and a processor executes computer executable components stored in the memory. An assessment component assesses a computer network, and classifies the computer network relative to M network classifications stored in a repository, wherein M is an integer greater than one. A risk component determines risk of vulnerability subject to change impact regarding protection against a computer virus or cyber-attack based on historical information regarding vulnerability exposure and vulnerability remediation changes relative to the classification of the computer network. A recommendation component that generates recommendations and best action to mitigate risk and impact, and remediate the vulnerabilities based on the risk assessment and business priorities.
    Type: Grant
    Filed: February 26, 2018
    Date of Patent: September 15, 2020
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Sai Zeng, Vugranam C. Sreedhar, Karin Murthy, Jinho Hwang, Milton H. Hernandez, Lisa M. Chavez, Muhammed Fatih Bulut, Virginia Mayo, Xinli Wang, Cindy Mullen