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  • Writer's pictureCristina Ferrero Castaño

Big Data analytics: why it is so important in cybersecurity

Security when using any device, surfing the Internet or registering on platforms must always be present. It is a very important factor and we must protect it. For this to be possible, it is important to have antivirus, to have updated systems or to avoid installing insecure programmes. But in this case we are going to talk about how Big Data analytics is very useful to avoid cyber threats.

Javier Jiménez

Redes Zone

January 9, 2022

Big Data analytics, an ally for cybersecurity

Big Data analytics can be said to be a variety of techniques for analysing large-scale data. This allows a wide variety of information to be obtained in order to make decisions or carry out improvements. It stands out for having a large volume of data, hence the name Big Data.

Big Data is generally complex to manage, process and even analyse. For this, advanced technology and tools are generally used. We are talking about having to analyse tens of Terabytes or even Petabytes of data, which is not possible using conventional equipment and systems.

Normally, different structured data are combined to achieve a large amount of information that can be analysed. This allows large companies and services to have a lot of data, a lot of information, and to make decisions, to know better how to act, what to improve, etc.

By analysing so much information, Big Data allows a company to obtain answers to a lot of data that could appear. It is used in all kinds of sectors, such as health, advertising, tourism... And yes, also in IT security, as we are going to see.

Why it is important in IT security

The first thing Big Data analytics does is to collect a large amount of data. It obtains raw information, whether structured or unstructured, from all kinds of applications, customers, services... We can say that this information is also collected from many types of devices, such as computers, IoT sensors, mobiles or cloud storage.

By processing such a large amount of data, it will have a wide range of possibilities stored for analysis, in order to detect possible attacks that may occur. Moreover, by analysing all this information, it can help to thwart possible attacks in real time.

Cybersecurity, by using large stored databases, can work on a large basis to detect possible vulnerabilities. For example, bugs that appear when using a certain Internet service, an application, etc. This can prevent many attacks and protect users.

It is very important for the simple fact that virtually any computer on the network is vulnerable to some kind of attack. Therefore, by being able to manage so much data and information, thanks to Big Data we can improve the speed at which we can solve problems.

Ways to prevent attacks

We can name some examples that can be achieved thanks to Big Data analytics and apply it to IT security. In this way, it helps cybersecurity experts to take preventive measures and solve potential problems, such as network attacks.

  • Creating models

The first thing that Big Data analytics helps with is to create predictive models that can serve as alerts. If something out of the ordinary appears, something that is configured in these models, it could serve as an alert so that action can be taken as soon as possible to prevent attacks.

Thanks to predictive modelling, artificial engineering and machine learning software can be used to ensure that a potential cyber threat does or does not enter a network. For example, in a company where a particular attack may break into systems.

  • Monitor

Something very important for security is to create rules. For example, create guidelines to check whether systems are up to date, run the antivirus regularly, check that installed applications are working properly... It is also important not to make mistakes, such as downloading a malicious file or leaving a device unattended, out of date or unprotected on the network.

Big Data analytics also helps to monitor and create large-scale automation systems. The aim is to constantly review what we have mentioned, alerting as soon as it detects that something is not complying with the established rules. It is a further help for those responsible for a company's IT security, for example.

  • Detecting attacks

Big Data analysis also makes it possible to create automated intrusion detection systems. This makes it possible to detect any movement made by an attacker. For example, taking advantage of a vulnerability. In this way we can solve the problem before it becomes more serious and actually serves to steal information or sneak malware.

Here we can mention real-time threat detection. This is very important to stop attempts to access a system. If a cybercriminal tries to break through security barriers, for example to access the wireless network or a computer remotely, this type of protection is very useful.

  • Analysing previous attacks

But if there is one thing that defines Big Data, it is the ability to analyse a huge amount of data. And this will make it possible to review all past reports of previous attacks. No doubt this, the experience with previous threats, will help protect systems and learn from the past.

For example, if an organisation has suffered a specific attack, it is possible to analyse that report to see how best to manage that protection.

In short, Big Data analytics is really useful for improving network security. It provides cybersecurity experts with a large database from which they can analyse reports on previous attacks, create predictive models or monitor possible attacks. This can prevent intruders from entering a network or help detect vulnerabilities.

However, to maintain security, especially at the user level, basic and common rules must be followed. For example, using antivirus software, such as Windows Defender or Avast, to name a few, as well as keeping systems properly updated. The latter will allow you to correct any vulnerabilities that may appear and could pose a threat. But undoubtedly the most important thing of all is common sense and avoiding making mistakes.

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