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5 Big Data Vulnerabilities You Could Be Overlooking

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Big Data Vulnerabilities

Big Data Vulnerabilities

Big Data Vulnerabilities-Nearly all data is either stored or passed through network related channels these days, increasing the potential for a major compromise. The elevated risk is just a byproduct of digital-heavy and internet-reliant operations in the modern world. Few organizations still maintain a local or private data system, with most opting to take advantage of the cloud.

Although there are many reasons for this, the most pertinent is the always-on and mobile-friendly benefits of cloud technologies. In addition, there’s an opportunity for organizations to take a step back and allow cloud providers to manage the more complex aspects of a network, including security, maintenance and more.

But it should come as no surprise that opening up the data and related systems to the greater internet also means introducing greater risk, particularly when it comes to system vulnerabilities. No system is perfect, which means it’s likely there is a way for its hardware or software to be compromised, in turn meaning that any related data can be stolen or manipulated.

To put it simply, big data systems are more vulnerable than you might think. This can and will affect your data, which means that employees, partners, and customers can all end up as collateral.

There are ways to better lock down systems — even cloud-facing ones — but you have to know what you’re looking for first. What vulnerabilities exist? What could you be missing? How can you protect your organization, your network and your data?

1. Back to Basics with The Big Three

When you’re talking about big data or cloud technologies, there are three stages that most systems deal with particularly when it comes to the flow of content.

Those three stages are:

  • Data ingress or data sources, which means what’s coming in and from where
  • Stored data, which means what’s staying and being stored
  • Data output or data sent, which means what’s going out to other parties, individuals, applications and tools

Immediately, you can see that any and all data is being routed in several directions, making it difficult not just to secure but also to track down. You must be able to see this flow of content — whether that’s in or out — as well as discern what parties are involved, what’s happening with the data and what it contains as far as sensitive information or details. Without any of these things, you cannot properly secure your content and or network.

For example, ingress data from an unknown source can flow into a system already compromised. The opposite can be true, as well, where data remains secure inside your network but becomes compromised upon leaving.

This is where you should start with any big data or network-focused system. Once you truly understand your data and how it’s affected by these three stages you can implement stronger security.

2. Administrative Authentication

When it comes to accessing sensitive content most administrators understand the importance of proper authentication and user access. Only the right people should have access to the information, and there must be controls in place to both prevent and allow access when necessary. This is also referred to as identity access management.

It’s easy to forget that big data administrators or cloud providers may also have access to your data. Theoretically, they could mine, view or manipulate the content without permission, and if there are no monitoring tools in place you’d be none the wiser. No notifications would come through about what’s happening.

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Article Credit: Inside BigData

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