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Big data analytics: why it is so important in cybersecurity

By analyzing so much information, Big Data allows a company to get 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 computer security, as we are going to see.

Why it is important in computer security

The first thing big data analytics does is collect a large amount of data. Obtains raw information, whether structured or not, from all kinds of applications, clients, services … We can say that this information is also collected from many kinds of devices, such as computers, IoT sensors, mobiles or also cloud storage.

To the process such amount of data, it will have a wide range of possibilities stored for analysis, in order to detect possible attacks that may occur. In addition, by analyzing all this information you can help stop possible attacks in real time.

The cybersecurityBy using large stored databases, you can work with a large base to detect potential vulnerabilities. For example, errors that appear when using a certain service on the Internet, an application, etc. This way they can prevent many attacks and protect users.

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

web crawling and web scraping

Ways to prevent attacks

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

Create models

The first thing Big Data analytics helps with is by creating predictive models that can serve as alerts. If something out of the ordinary appears, something that is configured in those Models, it could serve as an alert to be able to take action as soon as possible and avoid attacks.

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

Monitor

Something very important for safety is create some rules. For example, create guidelines to check if the systems are updated, run the antivirus periodically, see that the installed applications work well … It is also important not to make mistakes, such as downloading a malicious file or leaving a device neglected, without updating or unprotected on the net.

Big Data analytics also helps to monitor and create large-scale automation systems. The objective is to constantly review this that we mention, alerting as soon as it detects that something of the established rules is not being fulfilled. It is one more help for those responsible for computer security in a company, for example.

Detect attacks

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

Here we can mention the detection of threats in real time. 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.

Detect Phishing in real time

Analyze previous attacks

But if something defines Big Data, it is power analyze a large amount of data. And this will allow you to review all the past reports on previous attacks. Undoubtedly this, experience with previous threats, will help protect systems and learn from the past.

For example, if an organization has suffered a specific attack, it is possible to analyze that report to see how it is best to act in order to manage that protection.

In short, Big Data analytics is really useful to improve network security. It is used for cybersecurity experts to have a large database from which to analyze 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, and especially at the user level, basic and common rules must be followed. For example, use antivirus, such as Windows Defender or Avast, to name a few, as well as having the systems updated correctly. The latter will allow correcting possible vulnerabilities that appear and may pose a threat. But without a doubt the most important thing of all is common sense and avoiding making mistakes.

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