Big Data

Take advantage of all the opportunities
opened by the value-added exploitation of big data


SecuriteA Big Data solution is a true information system in itself, incorporating applications, processing components, networks, data storage… but with the unique feature that it calls on massive use of data from a wide diversity of sources, as well as distributed processing and storage resources.
Not surprisingly, the security measures required for this kind of environment are very similar to those needed to secure any information system. They fall into three categories: governance, protection and supervision. .


The introduction of a data analysis solution requires both a revision of existing policies to integrate new uses of business data and an extension thereof to incorporate issues specific to new data from different sources such as social networks and the analysis itself generating new high added value business data.


Depending on how sensitive the data is, confidentiality is respected by:

  • Ensuring close control over access to the data via an Identity & Access Management solution
  • Implementing, as a regulatory requirement, an encryption solution for the most sensitive data.

The recovery of activity trails, essential for security, is made possible by two technological developments:

  • The availability of large storage volumes for the mass production of activity trails for systems and users.
  • The development of analytical tools giving a new value to these trails while making them usable by the most intelligent security supervision systems.


With the emergence of Advanced Persistent Threats (APT), whose primary purpose is to smuggle recoverable data by the attacker, the integration of perimeter security measures is imperative. However, because of the new threats that may be able to circumvent these measures, simply monitoring these measures is just a matter of IT ‘hygiene’.

Thus, to tackle these threats effectively and more proactively, organizations need to use a second-generation Security Operations Center (SOC V2). This effectively allows all trails produced by the system to be monitored, correlated and analyzed, so as to identify even the weakest of signals, which might indicate that an advanced attack is in progress.

In this area, the analytical technologies introduced by big data provide a resources to complete the security arsenal by making supervision smarter and therefore more effective against specific threats.


EMC, Gigaspaces, MapR, Microsoft, MongoDB, Parstream, Pivotal, QuartetFS, SAP, Sinequa, Software AG, Tibco
Bull also works with many Open sources solutions in the Hadoop, NoSQL, newSQL and CEP ecosystem.


Livre blanc
White paper

Manufacturing – « What businesses can learn from big data and high performance analytics in the manufacturing industry’ »

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Big Data
S. Gelgon
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Sébastien Gelgon, Cybersecurity Manager, Bull
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