The way that we do business today is way different than the way we were doing business 20 years ago before the modern age hit us like a sack of bricks. Now, we live in a modernized world where big data is easier to collect and use to further a brand’s reach and disrupt industries in a manner that’s a lot easier than any of the others used previously. It has provided all marketers with the opportunity to make ad campaigns more consumer-centric and uncovering missed areas they should touch on. In fact, the big data industry will continue to grow in the coming years. Marketers are trying to leverage the constant growth of online use. But when you start using enterprise big data applications, security issues become the primary concern. This has led into further research into what can be done to uphold the privacy of those who the big data is about. At first it seemed almost impossible. Now, we’re able to give you the complete rundown with examples of what can be done to ensure the highest level of big data security possible. See for yourself.
1. A secure way to go about deployment of big data in business.
The first step is going to set the tone for the outcome. If you fail to implement it properly, you could create a massive security nightmare for your company. Take the time to deploy your big data system securely by following the steps outlined below. Big Data Cryptography for an Enhanced Encryption Level Encryption has evolved dramatically. With the onset of big data, it has become a lot more complex than ever. By using something like SSE (Searchable Symmetric Encryption), you can conduct searches on encrypted data. Once SSE or something similar is installed, you can use one of the encryption methods below. Attribute Based Encryption: Used for integrating access controls into encryption. Converged Encryption: Cloud providers are able to identify duplicate data via converged encryption using keys. Identity Based Encryption: Plain text can be used when you choose identity-based encryption. Designed to make key management easier within a public environment. Granular Access Control for Defined User Permissions You can define user levels or specific permissions for each user individually. This helps ensure that each user has the appropriate access level and no access where it’s unnecessary. This is often used in a professional environment to delegate big data jobs to employees. Initial Employee Training for Big Data Privacy Standards Making your employees aware of how you use your data and the privacy that needs to be embraced is the only way that you’re going to protect it. This is because you must make it aware what the policies are and what’s expected of employees right out the gate. No standards put into place leaves a lot of room for failure, whereas setting the tone leads to success. Make Sure You Use Secure Programming Frameworks There are many different frameworks used in big data, but there is also tons of security risks that come with it. In order to minimize liability, make sure that you take the necessary steps to secure your framework and prevent personal information from being put at risk of landing in the wrong hands. You can find out how to secure programming frameworks as well as other security measures by checking this post out on Techgenix. Think Outside of the Box for Added Security Whether inspired by a recent big data security breach or just something that popped up in your mind, embrace the opportunity to think outside of the box. Hackers are already doing it, so you must get on their level to beat them at their own game. Too many times, a breach could’ve been prevented if one just would have taken the time to think about new ways to secure data.
2. Using a VPN to securely access/transfer big data
Transferring information, especially personal information, puts your data at risk of being intercepted by an unauthorized party. In the early days of big data, enterprise network managers discovered how big of a risk it posed. This led to the art of embracing VPNs (Virtual Private Networks) to handle all the aspects of big data. From viewing it to editing it to transferring it, a VPN should always be used. No exceptions. The reason for this is that it helps encrypt it even further during transmission to ensure that only the right sets of eyes can view it. Not to mention, it makes it almost impossible for hackers to figure out how to hack into the system and obtain data they weren’t supposed to have. There are even free VPN providers, like this one here: https://www.hotspotshield.com/free-vpn/
3. Monitoring around the clock and performing a security optimization.
The only way that you can ensure your security practices are working like they should it to detect downtime as it happens. In addition, unauthorized access or other signs that your big data system may be in jeopardy. One thing that the introduction of big data has done to the world of computing is make security a more complex manner. This isn’t bad like a lot of the things that become complex, because the more complex it is the safer it is. In fact, many studies have been done to show the impact. If you truly want the best security precautions for big data, you have to know what’s going on. Of course, there are many other ways to secure big data like the ones that were featured here. They’re dedicated to innovative security measures that enhance the usage and modernization of the world of big data. While it may be a new tool in the world of business it sure has proven that it will not be going anywhere in the future. It is time to get used to it.
Big Data Security Must be a Core Priority
Big Data security is a major concern in 2019. You need to take all preemptive measures to guard against a potential breach. These guidelines should set you on the right path.