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Posted: June 8th, 2022
Cybersecurity Perspectives newsletter
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Cybersecurity Perspectives newsletter
Data science is increasingly being utilized to avert, identify, and remediate expanding and evolving cybersecurity threats. For the last ten years, FUD (fear, uncertainty and doubt) have driven companies (Patrick, 2018). In the end, data science is making it possible for the companies to shift from assumption to facts.
Data science is improving cyber security in multiple ways. For instance, it enhances the use of predictive and active intrusion detection systems. Cyber attackers utilize a variety of tools and intrusion techniques to obtain access. This is where intrusion detection systems become important, both of preventive and active range. These systems work to monitor users and gadgets on the network and point out activity that is dangerous. Data science enhances and simplifies the utilization of these tools (Sikos & Choo, 2020). By inputting current and past data into a Machine Learning algorithm, this system can accurately identify probable issues, and even predict prospective attacks and identify various loopholes over time.
Data science enhances the protection of valuable information. Currently, security measures such as encryption or highly intricate signatures are being used to safeguard confidential information. The involvement of data science makes it possible to create protocols that are impenetrable (Carrascosa, Kalutarage & Huang, 2017). For instance, by assessing the history of the company’s cyber-attacks, it is possible to use to build algorithms to identify the chunks of data that are mostly targeted.
Data science will make it possible to put focus on abnormalities that matter. Not every conduct that is somewhat unusual is going to be pertinent for purposes of cybersecurity purposes. As such, machine learning can help find patterns with abnormalities that could potentially turn to be larger threats.
With data science, it will be possible to conduct behavioral analytics. It is good to have the ability to detect and identify cyber attacks but comprehending the behavior of the attacker is another. With tools like Solarwinds Log and Event Manager (LEM), the company will be able to pull a big amount of data from various sources (Verma & Marchette, 2020). This way, loads of information can be processed on a timely basis and the malicious hackers are handled much simpler.
References
Carrascosa, I. P., Kalutarage, H. K., & Huang, Y. (2017). Data analytics and decision support for cybersecurity: Trends, methodologies and applications. Springer.
Patrick, R. (2018). Data science for cyber-security. World Scientific.
Sikos, L. F., & Choo, K. R. (2020). Data science in cybersecurity and cyberthreat intelligence. Springer Nature.
Verma, R. M., & Marchette, D. J. (2020). Cybersecurity analytics. CRC Press.
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