What Security Issues Come From Big Data? The 7 You Must Know

Most businesses nowadays are using big data to increase their efficiency. Why wouldn’t they? After all, big data has plenty of benefits to offer. For starters, big data helps in making better business decisions. It also helps in a better market analysis and improves the audit process. For instance, through big data, companies can analyze customer behaviors and make changes in their way of doing things. However, using big data comes with its own set of challenges. One of the biggest challenges is security.

In this post, we’re going to look at big data security issues in detail. We will also check out some measures to overcome these problems. In addition, this post will also provide an insight into the future of big data. So, let’s dive right in!

What Is Big Data?

Before diving into what big data is, let’s get to know what data is.

Data is an entity that a system uses to perform operations.

If you’re thinking that big data is rocket science, you’re wrong. In fact, it’s also data! Just with a massive size. In short, big data is the collection of loads of information which experiences exponential growth in size.

Big data is usually complex and is available in large quantities. It’s available in two forms: structured and unstructured.

As you probably know, normal data sets already have security issues if not stored properly. So you may be wondering: What are the security issues of big data? Let’s discuss in the next section.

Big Data Security Issues

We all know that firms generate huge amounts of data. They also have processes for analyzing the data. With such a huge amount of data comes a lot of security issues. And we all know that data security is of utmost importance nowadays.

Besides safeguarding the data, there is another thing you need to protect. Do you know what it is?

Analytics! Big data security refers to tools and measures. These tools guard information and data analytics processes from malicious activities. And, of course, we don’t have any shortage of those. These malicious activities include information theft, attacks, and more. Let’s take a look at some major big data security issues.

1. A Secure Environment

Data is often stored near the source for the following reasons:

  • Easier analysis and processing details.
  • Limitations in data transmission when stored at a different location.
  • Latency issues when distance with the storage facility increases.

But big data, by nature, has data sources generating a great deal of data worldwide, thus making the geographical distribution of big data diverse.

This distributed data demands additional security. This is because of the distributed workload, updates in setup, and traffic variation. For instance, suppose a company has customers using its cloud platform for data storage. The company has low visibility and restrictions in securing the data from a different location.

Are you planning to invest in big data? Check the security-related challenges if the data is distributed.

2. Fake Generation of Data in Modern Business

Most firms have a centralized database. You would agree that it’s important to keep a watch on who can access the database.

Do you realize what can happen if a hacker gains access? First, they can start generating fake data. After that, they can place the fake data in your company’s data pool. For instance, a retail firm can get wrong shipment reports. As a result, it can impact customers who are about to receive a shipment. What if you experience a loss in revenue?

You must have noticed that most businesses nowadays depend a lot on real-time analytics. Another important innovation that firms rely on is the Internet of Things (IoT).

And do you know what else these companies need to do to protect their data? First, they have to limit access to their database. Secondly, they should also be able to detect the generation of fake data.

3. Difficulty in Controlling Data Access

In most firms, you can grant each user a level of access depending on their role. This is known as granular access control. It increases the security of the database.

However, big data involves the handling of large data sets. This makes granular access control and maintaining dashboards more complex, thereby making your data more vulnerable to attack. Even if there is a breach, it will take longer for the security team to notice the breach.

4. Less Budget for Security

We all know that cyberattacks are increasing day by day. In light of this, you would assume that most companies would increase their budget for security. But that’s rarely the case.

In fact, most firms spend less than 9% of the company’s budget on security. As a result, this low budget leads to a compromise in the security of the company as a whole. Since the necessary resources aren’t there, a company will find it difficult to protect the data. According to experts, companies should spend 10% of their budget on security.

5. Concerns With Anonymity

Companies have detailed access to customer information. In fact, you must know how personal and sensitive information users are required to share. This includes contact details, address, and financial information, among other things. Moreover, some sites also track the behavior of customers.

Do you think all customers are comfortable sharing these details? Of course not! Don’t you think they think about the safety of their data?

Now, you might say that almost all firms have encryption and data masking practices in place. But are they always effective? Well, the answer is that these practices are not a foolproof solution to data privacy concerns. Hackers with the right equipment can decrypt sensitive information. This can expose a company to further risks.

6. Risks Involving Data Brokers

Now, let’s suppose a company leaves no stones unturned in protecting data. But we know that large companies with a huge amount of data take help from a third party, be it an external audit agency or a data center.

Things can get risky when firms share data with third parties. Moreover, the lack of regulations addressing brokered data adds to the risks. Holding brokers accountable if anything goes wrong is a major challenge. In case of a data breach, how will you prove that the broker is to blame?

7. Lack of Skilled Staff

We know that there are limited resources when it comes to big data security. That’s a con of using big data. But with skilled people to handle big data security, addressing security issues is possible.

However, a shortage of skilled staff is one of the biggest problems most firms are facing. There are very few data scientists in a company. The lack of data experts makes big data security even more challenging.

However, don’t let these security issues scare you away from using big data. With some best practices, you can resolve these security issues. Wondering what those are? Let’s discuss this in the next section.

How to Overcome Big Data Security Issues

Now, we have outlined the major big data security issues. Let’s check out some measures to overcome these.

1. Avoid Inside Threats

Often, the carelessness of employees can cause internal security risks. This can also happen if the employees lack knowledge. Therefore, educating the workers on big data security enable them to stay alert.

For instance, all employees should know the risks of using public WiFi, especially if they have company information on their device. Provide digital security training to all the employees. By doing so, you reduce the likelihood of an employee leaking sensitive data.

In addition to training employees, enforce data security compliance rules. Make sure that your employees follow these rules and policies. If an employee violates one of these compliance rules, issue a penalty. This may sound a bit harsh, but it’s the same mindset that dissuades you from breaking a traffic rule: If you’re caught breaking one, a cop will issue a ticket.

2. Proper Encryption

Using an encryption tool is a must for ensuring big data security. When a hacker doesn’t have the key, the data is useless to them. Encryption also protects information at both input and output. Data encryption is usually one of these types:

  • Using a public key to encrypt the data.
  • Using a private key, so only the person meant to access the data has the key and is able to access the data.

3. Analysis and Monitoring

Include tools for both monitoring and analysis in real time in your big data. This can curb big data security crises to a great extent. Monitoring tools result in the instant detection of network intrusion. However, make sure that you have the means to understand the difference between a real and false alarm.

What Does the Future Hold for Big Data?

If we take a look at the current scenario, most businesses are turning toward using big data. Big data holds a lot of sensitive information. That’s not new news, is it? But the downside is that there is still a lack of measures to protect data.

We have realized the benefits of using big data in business. It’s high time now that firms realize the importance of proper security measures. Only then can one utilize big data to its full potential.

There is one thing businesses using big data environments need to keep in mind. Big data security is a continuous responsibility. With a combination of refined security measures and smart analytics, big data has a bright future. Security solutions are available. Of course, full implementation of these security solutions still awaits. These security solutions will surely get smarter in the future! When that happens, using big data won’t be as risky as it is now.

So, what are you waiting for? Get rid of security risks one by one. Keep implementing measures to enhance big data security. Consistency is the key here. Follow the right approach to implement security. Once you’ve achieved that, nothing can stop you from unleashing the true power of big data!

This post was written by Arnab Roy Chowdhury. Arnab is a UI developer by profession and a blogging enthusiast. He has strong expertise in the latest UI/UX trends, project methodologies, testing, and scripting.