Data Science: The defender of cybersecurity

By CIOReview | Tuesday, December 4, 2018

Data science is the field which includes processes and systems to extract knowledge and insights from data in various forms, which is a continuation of data analysis fields as statistics, data mining, and predictive analysis. Data science continues to improve and advance. Data science helps the cybersecurity field to protect against attacks and identify suspicious behavior.

In cybersecurity, the goal is to identify threats, stop intrusions and attacks, identify malware and spam, and prevent fraud. Data from a wide range of samples is used to detect malware and spam. The goal is also to identify anomalies and abnormalities in user behavior that caused by an intruder and take preventative measures to stop the intrusion from getting severe.

Following are some of the ways cybersecurity can be benefited by data science:

Statistical methodology: The Statistical methodology is one of the parts of data science which uses mathematical models and techniques for statistical analysis of raw data. It extracts information from research data and provides various ways to assess the robustness of research outputs. The methodology is able to detect unusual behavior against statistical models of normality.

Predictive analysis: Predictive analysis predicts future by using numerous techniques from data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data. Cybercriminals constantly try to create innovative models and algorithms for cyber attacks. Data scientists are able to break this stalemate by having insights into data provided by predictive analysis.

Critical framework for cybersecurity: The potential of data science is overpowering, to cover this up, National Institute of Standard and Technology came up with a framework, to incorporate data science into security. There are some aims to achieve and to follow the objective:

•   Risk identification and assessment of consequences: Organizations evaluate their assets based on the probability of attack. By assessing the consequences of the attack the organizations should equip to develop appropriate models and action plans.

•   Intrusion detection: Organizations should develop a data-based system that identifies problems within the network, and trigger a response.

•   Response to intrusion: Data scientists should use their expertise to process and utilize information from an event of a data breach. The information help them to analyze the effectiveness of the response and solution of the breach.

Hacking is an evolving menace, and nobody knows what form it takes. But the advancements of data science promise the businesses and organizations to address their cybersecurity concerns.