Challenges of Big Data in Cybersecurity

With some of the biggest data breaches in history having taken place in 2019 alone, it’s clear that cyber-attacks aren’t going to disappear any time soon. From the Capital One banking data breach affecting over 100 million customers to the major breach of Flipboard potentially affecting over 1 billion users, the rise in cyber-attacks is hugely concerning for both businesses and individuals alike.

Alongside this, the amount of personal information processed by companies across the globe has increased considerably over time. Because of this, cybersecurity practices have had to become more advanced than ever before, and new methods of processing such large volumes of data needed to be introduced.

This is where the use of big data has the potential to be incredibly useful, as it can not only help to block any potential cyber-attacks but also helps to analyze huge amounts of data far easier than was previously possible. Despite this, there is still a long way to go before big data and cybersecurity can coexist in harmony. To find out why, continue reading.

Put simply, big data can be defined as a huge amount of structured and unstructured information that because of its large size, cannot be processed using traditional database and software techniques. It has become increasingly utilized by companies as a way of discovering patterns and trends in behaviour, while it also allows for advanced threat detection and machine learning.

According to Forbes, the big data analytics market was worth an estimated $203 billion back in 2017. As companies look to adequately protect themselves against the growing threat of cybercrime and handle ever-growing volumes of data, the value of the market will undoubtedly increase considerably as the years go by.

However, the rise in big data usage hasn’t gone unnoticed by online criminals, as many hackers have now made companies using big data their prime target. The growing number of data breaches to occur in recent years is a clear marker of the vulnerabilities of big data. But, just what exactly are the challenges of big data in cybersecurity? In the next section, we’ll delve deeper into exactly that.

Sustaining the growth and performance of business while simultaneously protecting sensitive information has become increasingly difficult thanks to the continual rise of cybersecurity threats. Therefore, it’s clear that preventing data breaches is one of the biggest challenges of big data in cybersecurity.

On a daily basis, countless sensitive records are processed by businesses across the globe. If this information was to end up in the wrong hands, the consequences could potentially be disastrous, as has been evident in previous data breaches including the ones mentioned earlier.

Traditional preventative security tools and technologies used for data mining purposes and for the prevention of cyber-attacks simply aren’t sufficient enough for many businesses – particularly ones which handle such large volumes of data. This is why big data analytics have become increasingly utilized by cybersecurity personnel.

However, another challenge faced by businesses is that the staff in charge of data analysis often don’t have the required knowledge to respond efficiently to any potential threats which may arise. But, as artificial intelligence (AI) and machine learning continue to be implemented and knowledge and awareness of big data increases, this will hopefully become less of an issue for businesses in future years.

Optimizing cybersecurity should be high up on the priority list of any business in the digital age, as not having the correct tools could possibly spell a catastrophe. This is why big data technology is becoming used by more and more businesses around the world, as it helps them to fend off any potential attacks from hackers prior to them actually happening.

However, unless the focus is placed on achieving optimal cybersecurity in big data, hackers could potentially gain easy unauthorized access to information processed using big data technologies. Therefore, it’s clear that big data has its advantages and disadvantages.