International Business Machines Corporation

Kyndryl, Inc.

Kyndral, Inc.

International Business Machines Corpora ! Ion

Sai Zeng

Muhammed Fatih Bulut

Constantin Mircea Adam

Jinho Hwang

Shang Qing Guo

Milton H Hernandez

Frederick Y Wu

Vugranam Chakravarthy Sreedhar

Brian L Peterson

Yaoping Ruan

Alexei A Karve

John Joseph Rofrano

Robert Filepp

Lisa M Chavez

Jun Duan

Maja Vukovic

Anup Kalia

Nikolaos Anerousis

Daniela Rosu

Christopher Charles Young

Rajeev Puri

Braulio Gabriel Dumba

Richard Jay Cohen

Bhavna Agrawal

Frederick Y-f Wu

Matthew X Staffelbach

Virginia Mayo

Virginia Mayo Policarpio

Cashchakanithara Venugopal

Chitra Dorai

Anuradha Bhamidipaty

Manish Mahesh Modh

Karin Murthy

Guan Zhang

Debasisha Padhi

Neeraj Asthana

Fabio Minoru Tanada

Ioana Boier-Martin

Steven Ocepek

Laurent Balmelli

Emrah Zarifoglu

Man Mohan Singh

Abdulhamid Adebowale Adebayo

Mitesh H Vasa

Nerla Jean-Louis

Anubha Verma

Vysakh K Chandran

Suman K Pathapati

Cindy J Mullen

Ramesh S Palakodeti

Umar Mohamed Iyoob

In Kee Kim

Ubaid Ullah Hafeez

Liang Liu

Bo Yang

Sambit Sahu

Ying Li

Thomas E Chefalas

Ashish Verma

Robert Evan Strom

Alla Segal

Anees Abdul Shaikh

Karthik Visweswariah

Hai Huang

Srinivas Babu Tummalapenta

Naga A Ayachitula

Mitchell Adam Cohen

Li Jun Xia

Frederick Yung-Fung Wu

Om Dadaji Deshmukh

Roy Jefferson Byrd

Mila Keren

Daniel S Riley

Qi Ming Teng

Kunwadee Sripanidkulchai

William J Hladik, Jr

Jose Gomes

Julia Rubin

Zhiming Shen

Rinku Kanwar

Shailesh Joshi

Ting Dai

José Gomes

Lilian Mathias Ngweta

Christopher Peter Baker

Maureen E Rzasa

Gary J Wright

Xinli Wang

Brian Peterson

Guan Qun Zhang

Laura Murphy

Cashchakanith Venugopal

Jose R Figueroa

Systems and techniques that facilitate automated health-check risk assessment of computing assets are provided that can generate a baseline health-check risk score that corresponds to non-compliance of a computing asset with a stipulated control, and can adjust the baseline health-check risk score based on a weakness factor of the stipulated control, an environmental factor of the computing asset, a criticality factor of the computing asset, and a maturity factor of the computing asset.

Automated health-check risk assessment of computing assets

Users of an endpoint remediation system can be assigned to different roles, from which they can request exceptions, approve exceptions, and/or enable remediation on endpoint devices. The compliance scanning and enforcing process can be automated, while allowing entities to request and/or approve certain exceptions. Therefore, security compliance for customers can be actively managed to provide visibility to the endpoint device compliance state at any time.

Testing and remediating endpoint device compliance controls

A content generation method includes receiving a control document comprising one or more control clauses, identifying actionable content for the one or more control clauses, generating a programming language template for the one or more control clauses, identifying a closest existing control clause from a database for each of the one or more control clause, identifying a programming language implementation of the closest existing control clause, identifying similarities and differences between the programming language implementation and the generated programming language template, and annotating the programming language implementation for the closest existing control clause based on the identified similarities and differences. The method may additionally include determining whether a closest existing control clause exists, providing the generated programming language template to a user responsive to determining that a closest existing control clause does not exist, and receiving feedback from the user regarding the generated programming language template.

Compliance content generation

A method for scheduling services in a computing environment includes receiving a service scheduling request corresponding to the computing environment and identifying a resource pool and a set of compliance requirements corresponding to the computing environment. The method continues by identifying target resources within the resource pool, wherein target resources are resources which meet the set of compliance requirements, and subsequently identifying a set of available target resources, wherein available target resources are target resources with scheduling availability. The method further includes analyzing the set of available target resources to determine a risk score for each available target resource and selecting one or more of the set of available target resources according to the determined risk scores. The method continues by scheduling a service corresponding to the service scheduling request on the selected one or more available target resources.

Compliance aware application scheduling

Systems, computer-implemented methods, and computer program products that facilitate vulnerability and attack technique association are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a map component that defines mappings between vulnerability data representing a vulnerability of a computing resource and attack data representing at least one attack technique. The computer executable components can further comprise an estimation component that analyzes the mappings to estimate a probability that the vulnerability will be exploited to attack the computing resource.

Vulnerability and attack technique association

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.

Converting between tabular and structured data formats

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.

Computer environment compliance

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.

Scalable operators for automatic management of workloads in hybrid cloud environments

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.

Dynamic re-composition of patch groups using stream clustering

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.

Efficiency driven data collection and machine learning modeling recommendation

A system, computer program product, and method to deriving a cost model and dynamic adjustment of the derived model responsive to dynamic modification of one or more of the resources in a hybrid shared resource environment. Resources and corresponding configuration information are collected while monitoring runtime utilization of resource performance. As changes to the resources are discovered, the changes are subject to an assessment. A hybrid cost model is derived and configured to account for the one or more resources. The derived hybrid cost model is leveraged to conduct a multi-dimensional resource evaluation of the assessed changed configuration information. Responsive to the multi-dimensional evaluation, a generated resource utilization optimization of the one or more resources is selectively implemented.

Resource and asset lifecycle costing

Testing and remediating compliance controls

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.

Modification of codified infrastructure for orchestration in a multi-cloud environment

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.

Detecting a root cause for a vulnerability using subjective logic in social media

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Yorktown Heights, NY, United States of America

Sai Zeng