DSPM son las siglas de Data Security Posture Management (gestión de la postura de seguridad de los datos), una tendencia emergente en la categoría de seguridad en la nube. Gartner define el DSPM en su informe Hype Cycle™ for Data Security 2022 como un proceso que ofrece «visibilidad sobre dónde están los datos sensibles, quién tiene acceso a esos datos, cómo se han utilizado y cuál es la postura de seguridad del almacén de datos o de la aplicación».

¿Cuál es la diferencia entre CSPM y DSPM?

CSPM y DSPM son dos enfoques diferentes de la seguridad en la nube. El CSPM permite a los equipos identificar y resolver los errores de configuración asociados a la infraestructura o los recursos de la nube, como los recursos informáticos, los almacenes de datos o las bases de datos, etc. Sin embargo, la CSPM (Cloud Security Posture Management) no entiende los datos. La DSPM (Data Security Posture Management), en cambio, es un enfoque de la seguridad en la nube centrado en los datos. Proporciona un contexto completo en torno a los datos en las nubes públicas, que luego se utiliza como base para optimizar los controles en torno al acceso,, la gobernanza y el cumplimiento de los datos sensibles

¿Qué es la revisión de la postura de seguridad?

Una revisión de la postura de seguridad es una evaluación general de las medidas, políticas y controles de seguridad de una organización. Las organizaciones llevan a cabo la revisión para examinar los riesgos y vulnerabilidades con el fin de mejorar la postura de seguridad de sus redes, recursos, activos y datos sensibles.

¿Cuáles son las cuatro áreas de la seguridad en la nube?

Existen varias áreas de la seguridad en la nube que las organizaciones deben tener en cuenta a la hora de salvaguardar su entorno y sus datos en la nube. Sin embargo, los siguientes son los componentes comunes pero esenciales que las organizaciones deben tener en cuenta: gestión de la postura de seguridad de los datos, gestión del riesgo de los datos, gobernanza del acceso a los datos y gestión de las infracciones.

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Gestión de la Postura de Seguridad de los Datos

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Data Flow Intelligence & Governance de Securiti ayuda a las empresas a proteger su entorno de streaming y los datos sensibles contra el acceso no autorizado y otras amenazas de seguridad.

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Monitor user access to data and enforce least privilege controls

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Discover shadow and cloud-native assets and accurately classify data

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Assess & improve compliance with security best practices frameworks

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Analyze breach impact & automate notifications to affected individuals

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Understand data lineage and secure real-time streaming data

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Build safe enterprise AI systems

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Data Vectorization and Ingestion
Extract info from complex Unstructured Files, convert it into AI-ready formats, and sync to vector databases

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Data Curation and Sanitization for AI
Transform raw, unstructured files into data ready for model training and tuning

View

Context-aware LLM Firewalls
Protect AI interactions with intelligent retrieval, response, and prompt firewalls

View

Unstructured Data Governance
Manage and govern unstructured data to enable its safe use with generative AI

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Govern data for safe innovation

Data Discovery & Classification
Discover shadow and cloud-native assets and accurately classify data

View

Unstructured Data Governance
Manage unstructured data to enable safe use with generative AI

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Data Access Governance
Monitor sensitive data access and prevent unauthorized use

View

AI Governance
Establish controls for safe adoption of AI technologies including GenAI

View

Data Catalog
Enable users to easily find, understand, trust and access the data they need

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Data Lineage
Automatically track changes and transformations of data throughout its lifecycle

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Conduct data quality checks and validation across various data types

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Automate data privacy operations

Data Mapping Automation
Manage your entire data mapping lifecycle and automate RoPA reports

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Comply with emerging AI regulations and ensure safe use of AI

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Automate your entire assessment lifecycle and demonstrate compliance

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