Pairing Big Data and Machine Learning to Mitigate Cyber Risks

Enterprise Security Magazine | Monday, March 25, 2019

Like many of the conflicts that we see in the world today, the number of cyber threats has grown exponentially in scope and size. These malicious activities becoming more sophisticated are harder to detect and mitigate quickly. Majority of the organizations are not able to keep up with the pace of cyber threats. Subsequently, advanced analytics became a go-to option to stay secure from risks. To better protect the assets big data and machine learning could pair together.

Information is being amassed from an ever-growing variety of sources, and big data analytics has already proven its value to some organizations. It is no surprise that cybersecurity is next. According to reports, by leveraging data analytics organizations are more likely to recognize a security incident within minutes of the event. Virtually any industry can utilize big data for better cybersecurity.

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It is often challenging to handle the sheer volume of cybersecurity in a timely manner while big data can lead to cybersecurity improvement. This could make it harder to achieve the type of visibility that organizations require in their security infrastructure. Adding machine learning to this equation can use big data more effectively and improve cybersecurity beyond measure. Machine learning solutions can scan data to generate a picture of historical patterns of behaviors. Businesses can use these capabilities to detect security vulnerabilities, identify a breach as it is happening and integrate information from multiple sources. Organizations can successfully thwart attacks by uniting these tools and decrease the chance of experiencing breaches.

When combined, big data and machine learning can provide dynamic threat maps and even predict the next attack. While real-time analysis has dramatically improved, there is still no robust platform to predict when precisely an attack will appear. Business should leverage a variety of machine learning and big data analytical tools to detect attacks early and prevent damage. Information from these tools will help organizations create a robust strategy to have the best advantage possible.

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