East-west traffic needs to be segmented and inspected, not just for blocking lateral movement of advanced persistent threats and insider attacks, but to secure the data itself, some of which can be sensitive if disclosed or leaked. Network security architectures need to evolve from perimeter or gateway security oriented to a multi-tiered, hybrid architecture where more east-west traffic becomes virtualized and abstracted with the adoption of server/network virtualization and cloud computing.
Last, there is Access. As part of Big Data, data is being archived for long periods. Who is authorized to access which data, and for what purposes? Often there is not just a single data set, but rather multiple repositories of data that may be combined and analyzed together. Each set of data may contain certain sensitive or confidential information, and may be subject to specific regulations or internal controls. Further, there is often not just one group of analysts or researchers, but over time many constituents seeking to gain different insights. A large pharmaceutical company provided a good example where their Big Data research efforts were open to not just internal employees, but also contractors, interns, and visiting scholars. For each of them, a separate analytics sandbox needed to be created, authorizing and auditing specific entitlements to identified data sets that could be accessed and combined.
In such context, IT organizations need to fundamentally re-think network security instead of taking incremental steps to meet evolving data center security needs. In many cases, the data center infrastructure itself is presently being consolidated and transformed due to not just Big Data, but ongoing cloud computing and SaaS initiatives as well. As part of this transformation, IT should consider an architecture that is:
- High-performance — support the larger volumes of data with higher network throughput and with high-speed ports (e.g. 40G/100G fabric) and high port density, but also be scalable and elastic to accommodate ever-growing data sets
- Secure — augment perimeter security with increased internal segmentation to secure east-west movement of data and monitor for advanced and insider threats
- Consolidated — integrate multiple security functions from core security functions like firewalling/VPN, anti-malware and intrusion prevention to advanced threat protection, strong authentication and access control
Finally, customer may consider the opportunities to leverage Big Data itself for better security. With more control and monitoring points being deployed throughout the network and the data center, plus with SIEM (security information and event management) and log management tools being able to aggregate increasing amounts of security logs and event data, more security analytics and insights are possible to better protect not only Big Data but also the data center as a whole.
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