Security Data Scientist is emerging as the front-desk leaders

Have you ever heard about the security operations center (SOC) resources? Well if not let me introduce you to it. The security operations center resources are need of the hour to rule out the adversaries. Such adversaries give rise to aggressive campaigns. The SOC resource makes the use of latest and the advanced technologies to overcome the adversaries. Today, there the market is witnessing an exponential growth for the skills of information security and cloud computing along with the data science skills.                  

How the world of the security data scientist looks?

The market is inundated with oodles of products to identify the known threats as well as the indicator of compromises. However, is it applicable to the unknown or the hidden dangers? Well, it is not. There is a negligible amount of protection against the unknown risks, and the zero-day exploits. Also, the newly identified vulnerabilities to have little or insignificant protection.

We do have multiple servers, databases, devices as well as the applications to furnish the enriched security log data. However, with such an enriched data the overall management of the blend of structured as well as the unstructured data becomes a whammy situation.

What does the Data Security Scientist stand?

The Data Security Scientists are the perfectionists. These geniuses have loaded with a robust knowledge of the networking security, IAM (identity and access management) and vulnerability management. The data security scientists are a perfect blend of conceptual understanding of the mathematics as well as the statistical concepts at the advanced level. To list a few of these advanced concepts are the linear algebra, probability distributions, differential equations, quantitative methods in addition to the inferential statistics.

These security data scientists pioneer the domains of sophisticated algorithms and in turn, give rise to advanced models. They possess the caliber to associate these complex concepts to the real security data sets. The security data scientists are proficient in the computer programming languages such as Python, Scala, R, and MATLAB.

Security Data Scientists have nurtured in the usage of big data technologies. Such big data technologies are inclusive of HDFS, Apache Spark, Elastic Search, and MapReduce. With the assistance of such big data technologies, the security data scientists masters the solutions for the enterprise level security data. Additionally, they are imbibed with the business knowledge to present the complex data visualizations. Such complex data visualizations represent the data relationships. The data relationships are inclusive of key performance indicators, scorecards as well as the metrics. The job of security data scientists is to present these data relationships to the senior business executives.

The core skills involved in the branches of mathematics, statistics, computer science, security fundamentals and business communications are as follow:

Mathematics: The competent skills learned by a security data scientist under the domain of mathematics include linear algebra, advanced calculus, probability distribution, differential equations, and quantitative method.

Statistics: The competent skills learned by a security data scientist under the domain of statistics include parametric and non-parametric testing, inferential statistics, regression, classifications, clustering, resampling, and segmentation.

Computer Science: The competent skills learned by a security data scientist under the domain of computer science include scripting language, big data concepts, natural language processing, database languages, data modeling and munging.

Security Fundamentals: The competent skills learned by a security data scientist under the domain of security fundamentals include networking security, security intelligence, management of the vulnerability, IAM, encryption.

Business Communications: The competent skills learned by a security data scientist under the domain of business communications include visualizations, logical analysis, relationships, metrics, KPI’s, business intelligence and others.

What analytical services does the security data scientists offer?

The present data scientists requirement of the security organizations is for the organization, enrichment and the transformation of strong security data sets. The security data scientists transform the security data scientists transform such sets into meaningful schema and models. Here the necessity lies in the understanding of the data relationship with the descriptive analytics. Such descriptive analytic are composed of correlated heat maps, cause diagrams, effect diagrams, frequency charts and the series of time. As soon as the transformation of data accomplished, it is cleaned and persisted in a well-documented format. Then, data scientists must impart training to the machine to acquaint knowledge from the old labeled sets of data. Once the learning process is complete, the outcomes can be predicted with the assistance of supervised machine learning process.

Selective organizations are recruiting junior security data scientists as well as the data analysts. These data geniuses are being hired for constructing the security dashboards as well as the models for simulations. These dashboards and the simulation models aid in analysis, monitoring and reporting with the help of business intelligence tools. The integration of the security organizations with the mainstream business urges the security data scientists to evolve and provide the analytical services to other companies. Such analytical services are inclusive of fraud analytics, behavior analytics, risk analytics, and recovery from disasters.

The security data scientist knows that false positive classifications, pattern analytics, topic modeling are the cases where the blend of robust machine learning and predictive type of analysis can clinch in the success for the businesses. In turn, these projects will lead to a simplification of the workflow. Also, it will automate the repetitive manual functioning and subsequently give rise to new insights into security data patterns.