Emc IP Holding Company LLC

Dell Products Inc.

Or Herman-Saffar

Amihai Savir

Stephen J Todd

Yevgeni Gehtman

John Lawrence Dalton

Anat Parush-Tzur

Elik Levin

Alana Brook Marcum Barker

In one embodiment, a method for verifying a user of an information handling system that includes: identifying, by a verification manager of an information handling system of a computing environment, one or more components of the information handling system; generating, by the verification manager, a static indicator associated with the information handling system based on the one or more components; verifying, by the verification manager, the static indicator; identifying, by the verification manager, the user of the information handling system; identifying, by the verification manager, a plurality of behavioral characteristics associated with the user; generating, by the verification manager, a dynamic indicator associated with the user based on the plurality of behavioral characteristics; verifying, by the verification manager, the dynamic indicator; determining, by the verification manager, a user accessibility associated with the information handling system based on the static indicator and the dynamic indicator.

Verifying a user of an information handling system

Techniques described herein relate to a method for identifying breakpoints. The method may include obtaining, by a breakpoint identification device, an entity group data set corresponding to an entity group; generating, using the entity group data set, an enhanced entity group data set comprising the entity group data set and a derived data item; performing a clustering analysis using at least a portion of the enhanced entity group data set to obtain a plurality of entity clusters; training a machine learning (ML) model using the enhanced entity group data set to obtain a trained ML model; using the trained ML model and a set of simulated entities to perform a breakpoint analysis; generating a breakpoint graph based on the breakpoint analysis; and providing recommendations to an interested entity based on a breakpoint identified using the breakpoint graph.

Methods and systems for identifying breakpoints in variable impact on model results

Techniques described herein relate to a method for identifying offline accounts for online adoption targeting, including obtaining an account group data set; generating, using the account group data set, an enhanced account group data set comprising the account group data set and a derived data item; obtaining, using a ML model and the enhanced account group data set, a key metric set; performing a clustering analysis using the key metric set and a portion of the enhanced account group data set to obtain account clusters; assigning a weight to a cluster of the account clusters; performing a similarity computation for an offline account of the account group using the key metric set and the portion of the enhanced account group data set to obtain a weighted similarity score; adding the weighted similarity score to a ranked list of weighted similarity scores; and providing the ranked list to an interested entity.

Sales productivity enhancement using offline to online account targeting preliminary class

An information handling system may receive a plurality of rules and a file for malware testing. The information handling system may apply two or more of the plurality of rules to the received file to determine a plurality of outcomes of application of the rules to the file. The information handling system may determine whether to classify the received file as malware or not malware by applying a machine learning model to the plurality of outcomes.

Malware detection using a machine learning model

At least one security incident indicative of at least one security event that may impact or has impacted one or more assets associated with an organization is obtained. A remediation recommendation is automatically generated for the security incident based on one or more of: (i) one or more remediation processes associated with one or more security incidents that precede the at least one security incident in time; and (ii) one or more values attributed to the one or more assets of the organization.

Automated security incident remediation recommender

At least one security feed indicative of at least one security event that may impact or has impacted one or more assets associated with an organization is obtained. The at least one security feed is automatically classified as being relevant or not relevant. The at least one security feed is automatically ranked in response to the at least one security feed being classified as relevant. The ranking of the at least one security feed is presented to an entity to make an assessment of the security event.

Automated security feed analysis for threat assessment

At least one security incident indicative of at least one security event that may impact or has impacted one or more assets associated with an organization is obtained. The at least one security incident is automatically ranked based on one or more of: (i) one or more rankings associated with one or more security incidents that precede the at least one security incident in time; and (ii) one or more values attributed to the one or more assets of the organization. The ranking of the at least one security incident is presented to an entity to make an assessment of the security event.

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Beer-Sheva, Israel

Or Herman-Saffar