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Being paranoid about Big Data Security no longer looks funny. The growing cyber security threats are making brands scared to the death. The article explains major challenges and best practices for Big Data Security.

Let me ask you a simple question, are you paranoid about Big Data Security? Well, you probably are now after a year worth of headlines like

• Pentagon to boost cybersecurity force in return to the recognition of increasing threats in cyberspace
• Homeland Security Council planning to take action before ‘Cyber 9/11’ strikes

The headlines are enough to make you unplug, but only if, that was an option. With Big Data becoming more and more accessible, the security and privacy concerns are increasing as well.  The collection of huge amount of heterogeneous data is not a big deal today. Data mining and sharing has become a common practice among marketers, researchers and organizations. However, the tools to supervise and protect this Big Data are not sufficient enough to integrate best security practices, reason being lack of adequate training and the inability to offer large scale data privacy and security. Moreover, we also lack the required policies that can guarantee compliance with current security and privacy approaches. Additionally, the current security and privacy technologies are continuously being breached, whether intentionally or unintentionally.

From security perspective, the major challenge in front of Big Data is the safety of user privacy. This giant cloud of Big Data contains highly sensitive personal information and therefore imposes a huge concern. Well, the reality is that Big Data can result into Big Data breaches and it will cost you both time and money. Securing this Big Data is no longer a luxury. But before that, let’s look into the common challenges of Big Data Security.

Major Challenges in front of Big Data:

1. The Big Data itself

Most of the organization today follow a common set of standard security policies no matter which type of data they are dealing with. Well, the biggest challenge of Big Data is 3Vs, Volume, Velocity, and Variety.

• Volume: The biggest benefit of Big Data concept is that it is able to manage huge amount of data while also making sense out of it. But with quantity, increases the vulnerabilities.
• Velocity: The second challenge associated with Big Data is velocity. Especially within high tech organizations where decision making based on this data need to be very quick. Such a situation demands a security solution that is real time not only to alert and monitor but also to block unauthorized requests.
• Variety: Lastly, since the amount is big, providing permissions to the right people for the right resources and data becomes more of a chore. How do you actually decide, which data needs more security, whom can I provide access to this particular resources, which level of security is sufficient for that particular resources, etc are some of the questions you need to ask yourself on the regular basis.

2. Environment

Environment is the second crucial challenge here. Let’s see how

• Multiple Layers: The Big Data environments of today are not as simple as traditional ones used to be. It was quite simple to understand to identify blocking points, today we have got various layers from distributed storage to management system. The complexity is way much higher than the traditional systems making it very difficult to keep up with security.
• Multiple Technologies: With every Big Data environment, you need to deal with various technologies like NoSQL, BI tools, Data Warehouse etc. All these technologies are interlinked with various environment, which is again why providing Big Data Security is not as clutter free as before.

3. People

Last but definitely not the least challenge for Big Data is the people. Do you know people are often the weakest link when you talk about security, especially when associated with Big Data. When you think about the people who actually have to deal with Big Data and its administration, you are talking about PhD, computer scientist types. These people has major focus on anything but security. They completely dedicate themselves to making the product faster and accurate.  But the last thing in their mind is security and that too, privileged access management.

Securing Big Data with Even Bigger Security Practices

1. Security of application software

Big Data techniques were never initiated with security in mind, which is why you must use secure version of every open-source software. By using technologies like 20.20x version of Hadoop or above or Apache Accumulo one can address this issue. Moreover you can make use of proprietary technologies like Cloudera Sentry to provide robust security at application layer. These technologies also help in role-based access control to boost security for NoSQL databases.

2. Audit Log Maintenance, Monitoring, and Analysis

The next step is to introduce audit logging solutions in order to monitor and analyze Big Data clusters. Always keep in mind that you need to assign this task of monitoring and analyzing these files to a security engineer. To keep a secure database, consistent auditing, maintaining and analyzing logs is must.

3. Hardware and Software Configurations Security

Always build servers based on the secure solutions of your business’s Big Data architecture. Make sure that patching is up-to-date and that only privileged users have the access to critical resources

4. Account Monitoring and Control

Always impose strong authentication policies. Authentication is the front door for your hackers to get into your brand’s treasure and yet not many organizations put much focus on it. Introduce strong password policies, ask users to keep changing their passwords after regular intervals, educate them to not share passwords with anyone else. Moreover, you can also introduce two-factor authentication solution (2FA). The implementation of 2FA makes sure that the user needs to go through multiple security verifications in order to get the access. Although not 100% secure, the solution has proven to be a great way of reducing cyber criminal threats.

So guys, if you are serious about Big Data Security (Which I’m sure you are), you need to take these practices into consideration. Cyber criminals are not going away anytime sooner and that’s why you can’t afford to take Big Data Security lightly.