How to Use Big Data Analytics Against Rising Cyber Security Attacks?

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Big data and big data analytics have many implications across verticals. The use cases range from optimizing operational efficiency and price optimization to social media analysis and data warehouse offload.

One of the newest fields of applied data analytics is called cybersecurity. In other words, organizations started using big data analytics to minimize cybersecurity risks, prevent cyber attacks, and keep hackers at bay.

One question remains, though. How to use it against rising cybersecurity attacks? To help you out, we have to dig a little deeper into this topic.

Why is cybersecurity a big issue for all businesses?

There are two groups of reasons why cybersecurity is a big issue for all businesses. One group is more evident than the other. One of the most apparent reasons is the damage a cybersecurity attack can cause to an organization. It can ruin its reputation, corrupt data vital for business processes, and leak confidential information.

The other group of reasons is more subtle. Take any organization you want and compare its digital footprint today with the one from just five years ago. Whether it is a small, medium, or enterprise organization, today’s digital footprint is significantly larger than in the past. This means more entry points into the organization’s network, copious amounts of log data, and more devices to control.

Finally, we also need to address the nature of cybercrime. Cyberattacks are evolving along with technologies. Cybercriminals are always looking for new vulnerabilities to exploit. Thus, reaching the ultimate cybersecurity is borderline impossible.

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Big data as a solution?

How can big data analytics be a solution to such a complex problem? Data analytics for cybersecurity offers different solutions. Their application field varies as it depends on the type and source of big data that is being analyzed.

For instance, some networks and servers generate logs in real-time. These logs are the big data we are talking about. There are specialized tools that can go through the logs in seconds to detect anomalies and inform the IT department.

Most security solutions are cloud-based today. All of them generate reports about the cyberattacks that take place all over the globe. Security information tools use big data analytics to extrapolate cybersecurity alerts relevant to organizations in specific verticals.

User activity is also being logged. Analytics can help detect suspicious and unusual patterns in user or device activity, notify the IT department, or automatically initiate a device or user block. As you can see, big data offers not one but several ways to tackle the cybersecurity challenge.

How to Use Big Data Analytics Against Rising Cyber Security Attacks?

Visualizing threats

Risk assessment is essential for winning the war against cybercrime. Cybersecurity risk assessment reports are what cybersecurity professionals in IT departments use to decide which tools to use and how to set up security. However, due to scarce data, these reports are usually only partial and unable to communicate the scope of a real threat.

Data analytics for cybersecurity is usually embedded in modern cybersecurity tools. These tools use the data gathered from all points and recorded in the cloud to deliver massive and insightful reports. These reports feature the class of cybersecurity threats and the intensity of each threat individually.

Visualizing threats becomes easy when you can see data sources and threat patterns. On top of that, these tools come with a statistics module you can use to analyze historical data further and compare it against the current data. You can identify patterns and trends and make data-driven cybersecurity decisions.

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Predictive models and how to use them

Analytics enables organizations to use big data and pursue intelligent cybersecurity solutions. Thanks to analytics, experts can identify patterns in cybersecurity attacks. They can practically trace the hackers’ actions from the entry point to the target. This enables them to build predictive models for each type of attack despite its scope.

AI and machine learning play an important role as they can identify the patterns much faster, given that we are talking about the big data here. Predictive models offer organizations a proactive approach when it comes to thwarting malware and hackers.

Instead of alerting the IT department that there is currently an ongoing cyber attack, predictive models paired with AI and machine learning can prevent them from happening. As soon as they see an entry point that is an imminent threat, the cybersecurity experts receive a notification so that they can act accordingly.

How to Use Big Data Analytics Against Rising Cyber Security Attacks?

Testing your security measure with penetration tests

The problem with cybercriminals is that they can find a weak spot in an organization’s IT infrastructure even if it is kept tight. This is when penetration testing comes in handy. The goal of penetration testing is to simulate a cyberattack to test the resilience of the targeted infrastructure. This is one of the best ways to identify exploitable vulnerabilities.

Penetration tests also generate logs that can be subjected to big data analytics. Furthermore, it can help you refine your strategies and pinpoint exactly which security measures and policies should be implemented.

There is also one more thing. Penetration tests often don’t consider risky user behavior and device use cases, not to mention potential threats. When paired with big data analytics, penetration tests can provide a complete insight into infrastructure security. The synergy can also help organizations assess the viability of implemented security measures and identify which security layers need to be added to minimize the risk of a cybersecurity breach.

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There is no question that cybersecurity is one of the most significant issues for all businesses. However, employing data analytics for cybersecurity enables organizations to change their perspective on cybersecurity.

Thanks to big data analytics, organizations can visualize threats and use predictive models to keep their processes and data secure. More importantly, it can help businesses implement an ongoing cybersecurity strategy, which appears to be the only viable way to tackle the ever-evolving cybersecurity threats.

The post is written by the awesome guys over Data Entry Outsource

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