El Big Data también supone una revolución en el campo de la ciberseguridad

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CLAVES

  • A día de hoy, la revolución del Big Data afecta ya a prácticamente todas las empresas. La innovación tecnológica y la proliferación de fuentes de datos permiten analizar ingentes cantidades de información que puede ayudar a la empresa a predecir el comportamiento de los consumidores, maximizar la rentabilidad de las inversiones, etc.
  • Pero todo esto, a su  vez, cambia el panorama de la seguridad, ya que da pie a nuevas vulnerabilidades y abre nuevas vías a los atacantes.
  • A medida que aumentan las amenazas cibernéticas, las organizaciones más punteras se están dando cuenta de que uno de sus mejores recursos para luchar contra ellas es el creciente número de datos que tienen a su disposición, y el creciente poder de la tecnología para actuar sobre esos datos.

Toda organización de hoy en día está abrumada por los datos. No obstante, la recolección de datos no es algo nuevo: las empresas han registrado datos sobre contabilidad, finanzas, operaciones, suministros y clientes desde hace mucho tiempo. Lo que sí es nuevo, y que hace que el Big Data sea distinto, es la tecnología que proporciona al negocio la habilidad de recoger y usar esta información de nuevas maneras.

En primer lugar, cabe destacar que la tasa de generación de datos se ha incrementado exponencialmente conforme han surgido tecnologías que permiten registrar datos antes imposibles de monitorizar. El crecimiento de las fuentes de datos es muy amplio, y va desde las redes sociales, hasta los registros SQL, los registros del firewall, etc. Muchos de estos datos siempre estuvieron ahí, pero las compañías no fueron capaces de registrarlos hasta que se desarrollaron nuevos métodos y tecnologías.

En segundo lugar, el crecimiento de las fuentes de datos se ha traducido en un aumento en el volumen de datos que las organizaciones tienen que tratar. Gracias a la caída de los costes de almacenamiento, ya sea en servidores propios o alojados en la nube, todos los datos son registrados por un tiempo indefinido, al contrario que antes, que debían ser eliminados periódicamente ante la escasa capacidad de almacenamiento y procesamiento.

En tercer lugar, la tasa de generación de datos y el creciente número de fuentes se han traducido en una mayor variedad de tipos de datos, que van desde los altamente estructurados hasta los desestructurados. Históricamente, la mayor parte de los datos disponibles para el análisis estaban en formato numérico. Hoy, los datos que resultan almacenados pueden ser de todo tipo.

El Big Data, durante un tiempo, solo estuvo al alcance de algunas selectas empresas multinacionales y agencias gubernamentales, pero ahora, la avalancha del Big Data está impregnando a la mayoría de las empresas. El problema no es el tipo de datos, su monitorización o su almacenamiento, sino cómo se tratan esos datos. Para impulsar el valor del Big Data, las organizaciones recurren a análisis de comportamiento de los clientes, de forma que puedan tomar mejores decisiones, minimizar costes, maximizar la rentabilidad de las inversiones, y optimizar las operaciones. Pero es muy importante destacar que la seguridad de esta información ya no puede ser pasada por alto.

La seguridad, y en concreto la ciberseguridad, son a menudo consideradas como una de las principales preocupaciones para gerentes y líderes de las organizaciones del sector público y privado. En nuestros días, las nuevas tecnologías están cambiando la forma en la que las organizaciones operan e interactúan con empleados, clientes y ciudadanos en general. Permiten ofrecer operaciones más eficientes y eficaces, pero también cambian el panorama de la seguridad, ya que dan pie a nuevas vulnerabilidades y abren nuevas vías a los atacantes. Las empresas necesitan un nuevo conjunto de soluciones de seguridad suficientemente flexibles para adapatarse a los cambios tecnológicos e igualar el nivel de los ataques a los que deben enfrentarse. Esto plantea retos importantes, como los siguientes:

  • Escalabilidad. El análisis del comportamiento de los consumidores requiere una rápida monitorización de los datos procedentes de múltiples fuentes, lo cual implica un crecimiento exponencial de los datos almacenados.
  • Optimización. Procesar rápidamente los modelos analíticos para tomar una decisión es también un foco de problemas.
  • Experiencia. Más allá de la tecnología en sí, el mayor problema al que se enfrentan las instituciones es la falta de habilidades para configurar y ajustar los motores de análisis, interpretar las ideas generadas y actuar de acuerdo con las potenciales amenazas detectadas.
  • Integración. La computación en nube ofrece ventajas signifivas para el análisis especializado de datos. Las empresas deben definir cuidadosamente sus estrategias de seguridad para lograr un equilibrio eficiente entre las necesidades de los empleados, la integración y las necesidades de gestión.

Todas las organizaciones seguirán luchando por integrar soluciones tecnológicas, y por combatir los ataques cibernéticos, que se marcan como objetivos la información financiera, la reputación y las políticas de gestión de las instituciones. Para mejorar la seguridad y reducir el riesgo, las empresas deberían seguir algunos consejos:

  • Aprovechar las fuentes de datos existentes. Las organizaciones tienen una gran cantidad de datos que podrían aprovechar para mejorar la seguridad, como por ejemplo los registros de actividad en red, la información NetFlow, los registros SQL, etc. Pero las empresas necesitan hacer un recuento de cuáles son las fuentes de datos disponibles de estas características, cuáles son accesibles, etc.
  • Contextualizar y conectar los datos. Una vez que la organización entiende los datos que tiene, debe ponerlos en su justo contexto y relacionarlos con otros datos, creando una red de información. Esto crea una imagen bastante clara de los riesgos y amenazas para la organización.
  • Utilizar análisis profundos para perfeccionar la imagen. Entender el contexto de los datos y conectarlos es solo el principio del proceso, pues luego es fundamental perfilar esa imagen más general y abstracta a través de análisis profundos, métricas útiles, información relevante y recomendaciones adecuadas.
  • Pasar de la respuesta retroactiva a la proactiva. Una vez que el análisis de datos está realizándose con éxito, debe porcederse a la evaluación en tiempo real, de manera que las amenazas sean mitigadas de forma proactiva, antes de que se produzcan los ataques como tal.

A medida que aumentan las amenazas cibernéticas, las organizaciones más punteras se están dando cuenta de que uno de sus mejores recursos para luchar contra ellas es el creciente número de datos que tienen a su disposición, y el creciente poder de la tecnología para actuar sobre esos datos. Con el crecimiento de las capacidades analíticas y predictivas, las empresas pueden identificar y responder a las amenazas que plantea la nueva era digital.

 

Documento completo: Big Data and Predictive Analytics: On the Cybersecurity Front Line
Fuente: IDC
Fuente: IDC

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