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Integration of Data Science into Cyber Security and its impact

Data science is a term or a discipline that is used to refer to the field that deals with using scientific methods, algorithms, processes, and systems with the aim of extracting knowledge to make meaning out of large complex data that can either be structured or unstructured. In simpler terms, data science is simply the study of data.

Data science, therefore, provides for the opportunity to bring together in application different fields in statistics plus computation to help interpret data which consequently helps in decision making. Hence data scientists convert big data into information that not only gives meaning but becomes usable.

Data Science and its integration to Cyber Security

Among the many areas, data science becomes and proves extremely useful is in cybersecurity. Before the integration of data science into cybersecurity issues, cybersecurity analysts and experts would work and make decisions from a point of assumption due to a lack of clear and well-stipulated data. This would expose cybersecurity protocols into laying strategies for organizations that were not well informed but with the blind hope that they will work.

The entry of Data Science integration however tilted the boat to their favor because decisions would be made and strategies formulated from a more informed position and factual approach. The effect and impact of this integration have profoundly become great and continues to be felt across the hallways of cybersecurity.

Benefits and Impact of Data Science integration in Cyber Security

  1. General improvement in detecting intrusion into networks and at the same time enhancing the abilities of a computing system to predict an intrusion. Data science has been a game-changer in that it helps organizations feed their networks with algorithms that help learn, understand, and carefully predict how and when an attack happens or can happen.

Cybercriminals are known to change their attack methods and though knowing their exact next move may be hard, a network can be empowered to be able to detect these moves and consequently providing a gap of response before the cyber criminals hit their target.

  1. Providing algorithms that help detect loopholes in a network. By identifying these loopholes, data science, therefore, ensures an organization closes them up and hence beefing up their cybersecurity to their advantage.
  2. Data science tools such as Solar winds Log have helped predict the future behavior of attacks by helping use the large data they pull and correlating them with network logs.
  3. Supporting and reinforcing measures such as encryption put in place by organizations to secure data. Data sciences traditional ways of ensuring cybersecurity by building and establishing impenetrable protocols that are put in place using algorithms that learn a machine.
  4. Data science also helps organizations run and test their networks against real-world scenarios rather than reliance on simulation data developed in a technological laboratory. With this, they can be able to see real scenarios of a data breach and how they were detected or handled.

How the future looks 

With increased interest and integration of Data Science in attaining cybersecurity, this inter-relationship only promises to get better and at the same time offering cybercriminals a run for their money. Increased integration will mean the development and deployment of better and sharper tools and algorithms which will help not only to detect faster but also to completely close loopholes that have been used in the past.

These developments would mean therefore an opportunity for individuals involved in Data science and cybersecurity to not only hone their skills but to also create better and move effective systems as they help the world to navigate the rough and messy waters of cybercriminals.