Top 3 Areas of Concern for Enterprise Security
Information is vital to today’s businesses. Some are calling it a currency, meaning that it has a lot of value to everybody concerned. Businesses are mining data to understand their customers better, to stay competitive and on top, or to create new data-based products that they could sell.
And these information and data are coming from different sources. Internet commerce and social networking are both ushering in an age of more data. In fact, the data that comes from these two sources can be overwhelming. Smartphones, other mobile devices and the Internet of Things are also contributing largely to the explosion of data. Other fields where data is just exploding are in the areas of research, medical, scientific and consumer data.
With the influx of data from all over, how does it affect enterprise security? There are three areas of concern.
- Companies are opting to store big amounts of data in a central location, this will help them get all the data that they can and analyze these later on. And for some companies, this means that they would need to upgrade their systems to handle and transfer this much data. It also makes your perimeter security vulnerable to attacks, because most vendors and service providers are not equipped to handle that many sessions or large transfers.
- Big data flows are not uniform. The amount of data going in may not be the same as the amount of data going out, in terms of volume or form. Big data is changing data flow within the data center with more lateral traffic rather than those going into the Internet or into other systems. Lateral traffic needs to be secured to prevent insider attacks and persistent threats, as well as securing the data in the data center. This may entail a redesign of network security architecture to include both perimeter security and a multi-tiered architecture that would allow lateral traffic to be virtualized should you choose to get into the cloud.
- Big data means that you will be gathering and storing data in a variety of repositories and each one of these repositories will have its own rules for access as well as internal controls. Plus the fact that you will have different end users with different goals looking for different insights from different data sets. That would mean that you would need to create different analytics sandbox for each of these situations.
Be sure that your big data architecture has the following characteristics:
- High-performance. You need to be able to support bigger data volumes as well as high speed ports and higher network throughput and high port density. It should also be elastic and scalable to ensure that you are able to handle burgeoning data sets.
- Secure. Segment lateral data while fortifying perimeter security. This will help you be guarded against both internal and external threats.
- Consolidated. This means that you should integrate various security functions from basic security functions such as anti-virus, VPN, and firewalling to advanced security tactics, access control and advanced authentication.
Need help securing your big data systems? Check out Four Cornerstone and our Oracle consulting in Dallas. We can provide you with a team of Oracle and security experts to work with you.
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