Cybersecurity is at a critical turning point, especially in the wake of the global lockdown that caused companies worldwide to conduct more online business than ever before. No organization is immune to data breaches, as hackers are using more sophisticated techniques — such as artificial intelligence — to perform these cyberattacks.

That’s why most cybersecurity tools are now leveraging data science and machine learning in antivirus software, comprehensive proactive security tactics, and more. Modern technology can search through data patterns to figure out where companies are vulnerable and help to eliminate the risk of attacks.

This article will walk you through everything you need to know about data science and cybersecurity. We'll show you which AI algorithms can help inform your AI data science and data analysis strategies to tighten up your cybersecurity.

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Table of Contents

  1. What is Data Science?
  2. What is Machine Learning?
  3. What is Applied Data Science?
  4. What is Cybersecurity Data Science? 
  5. How Applied Data Science and Machine Learning Work Together to Improve Cybersecurity
  6. The Bottom Line

What is Data Science?

Data Science is a branch of knowledge that deals with analyzing data. Data scientists look into the properties of data and data sets to determine authenticity, originality, and security. If your company uses data science effectively, it can boost security by predicting various risks. This is one of the most effective approaches to risk assessment that your organization can take. 

After an extensive data analysis, data scientists will work with other professionals to develop algorithms that block the threats of attack to your organization. The algorithms then inform the artificial intelligence and machine learning systems. Bringing machine learning into the mix can help you invoke a more targeted security approach.

What is Machine Learning?

Machine learning is a type of artificial intelligence with the ability to learn and make informed choices from data provided or past experience. Machine learning continuously improves the accuracy of results as scientists gather and analyze more data. 

What is Applied Data Science?

We live in a world filled with enormous amounts of data, but the raw numbers don’t tell us very much. With the techniques of data science, both machine learning tools and humans can reveal and interpret data findings and then put these lessons to practical use.

Applied data science refers to the way machine learning tools make use of data. When the algorithms developed from raw data are used to update AI and machine learning systems, you create a more targeted security approach that guarantees a relatively strengthened security system. 

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What is Cybersecurity Data Science? 

The central idea behind cybersecurity is data security. Cybersecurity data science is a relatively new method of implementing data science to detect, prevent and reduce cybersecurity threats. Most cyber-attacks compromise an organization’s stored data and put it to use in fraudulent activities. Cybersecurity uses data science to keep digital devices, services, systems, and software safe from cyberattacks. 

Large amounts of data can be difficult to manage without the help of data scientists. Using data science to analyze big data is an effective way of identifying financial and other types of security risks and proactively averting cyberattack plans. This kind of analysis gives data scientists a platform to make recommendations for how to detect threats. A predictive approach increases the efficacy of security measures surrounding sensitive data and makes the system exceedingly resistant to infiltration.

How Applied Data Science and Machine Learning Work Together to Improve Cybersecurity

As the use of technology rises, the process of securing large systems becomes more complicated. Additionally, an increasing number of organizations are collecting, processing, and storing highly sensitive consumer information. This has increased the threat level from cybercriminals who want to acquire this data for criminal activity.

Data science has had an impressive effect on cybersecurity, as evidenced by the following:

Improved Intrusion Detection and Prediction

Hackers have a variety of ways they can intrude different systems. And they are notorious for constantly changing their tools, styles, and methods to make themselves harder to catch. That’s why early intrusion detection is critical. Using data science helps organizations supply machine learning algorithms with current and historical information about such intrusions. 

This kind of analysis finds patterns that help detect intrusions so organizations can better manage their systems and predict future attacks before they happen. With machine learning algorithms, you can detect loopholes in your security environment before hackers can. 

Data Protection

Traditional security measures help an organization reduce its susceptibility to attacks. But data science helps reinforce these security measures even further. With applied data science, organizations have the chance to develop impenetrable protocols via machine learning algorithms. 

Behavioral Analytics

Detecting and identifying malware is an important first step in preventing attacks. But you also want to understand the hacker’s behavior. With a combination of data science and machine learning tools, an organization can amalgamate different data sets and find correlations in the system and network logs. This uncovers patterns that make it easier to predict a hacker’s future behavior, thus allowing your organization to implement the best prevention measures. 

More Accurate Predictions

Data science lets companies develop real-world hypotheses about security risks instead of making educated guesses in a laboratory. This helps organizations understand their security landscape better and collect data more quickly — and from a wider range of samples — to better inform deep learning and training on detecting malware and spam. This helps ensure fewer false positives regarding spam and malware detection, so you can set up better preventative measures. 

The Bottom Line

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No matter how large or small your business is, you need the right measures in place to guarantee your clients that their data is secure. The challenges posed by cybercriminals and hackers are greater than ever. However, combining data science and machine learning in your efforts can take your cybersecurity to a whole new level.

If you need to tighten up your cybersecurity, contact Xplenty for a 14-day demo and see how we can help you keep your data safe.