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Uses of Big Data Security Analytics in Preventing Cyber Attacks

Russell Thomas, Enterprise Security Mag | Tuesday, August 31, 2021

The ongoing digitalization of the business world is putting companies at risk of cyber-attacks more than ever before. Big data analysis has the potential to offer protection against these attacks. So, securing big data becomes pivotal for organization, for its better future.

Fremont, CA : Computers rule today's world. Gone are the days when people would sit with files and paperwork and stack up on important documents and such. With successive growth and expansion, organizations want to be based more and more on numbers- percentiles, probabilities, which would depict their sales reports and other such data. Thus, Big data comes into play and companies employ more manpower to build data extraction and aggregation tools. Big data allows the advantage of helping large companies modify their products to suit the needs of the buyers, recognize the marketing flaws and exchange data with other business corporations worldwide.

But alongside these big legit organizations run an equally enormous set of cybercrimes. This can be very destroying for the companies when their security is breached by cyber attackers. However, the ongoing digitalization of the business world is putting companies at risk of cyber attacks more than ever before. Big data analysis has the potential to offer protection against these attacks. So, securing big data becomes pivotal for an organization, for its better future. Here are some of the benefits of big data analytics for security incidents.

1. Machine Learning Predictions

The learning algorithms of the machine, along with security system data, may be used to examine historical and current data for threat assessment and prediction. This method helps in finding touchpoints of attackers before any attacks are executed. In addition, it can assist in responding to data infringements in real-time. These algorithms can correlate information automatically to identify a pattern of vulnerability. For instance, anomaly detection, malware detection, and look-alike predictions are popular use cases.

2. Scale automation and surveillance

The quantity of workers in any particular business causes a huge number of cyber threats. In many situations, employees do not know about cyber risks and do not know how to respond in different scenarios, thus attackers might be easily targeted. Big data analytics can assist in monitoring the wide range of user/system activity to avoid risks. This can avoid several data violations. Security professionals can also automate this procedure to minimize data infringements and in the event of an attack to speed up the recovery process.

3. Real-time intrusion detection

In real-time it is difficult to monitor and track vulnerabilities, however large data analytics can alleviate this problem by automating this process on a large scale. With real-time analytics, Intrusion Detection Systems (IDS) is further strengthened to identify any malicious activity in the system. These systems stop threats before illegal access to the system is provided to an attacker. For instance, organizations might integrate other proxy logs, good/safe domains and monitor system health.

4. Reporting on risk management

Security insights are vital if organizations want to retain their cyber defenses, then analytics and reporting can precisely aid them. Big data analytics gather actionable information from many sources and systems in order to assist in the investigation of fundamental causes.

Cybersecurity data analysis can function efficiently and can really enhance businesses' capacity to deal with attacks and data violations. Big Data Analytics can facilitate better detection, risk management, monitoring, and automation. Machine learning algorithms can help with the analysis of threat patterns and predictions.

See Also :- Top Data Security Companies