Importance of Cyber Security Data Science

30/09/2020 15

A few years have passed since that sentence in an Economist article said “the world’s most valuable resource is no longer oil, but data“, although this idea had already been coined in 2006 by a famous mathematician. All technology companies lead the use of this data, and in turn, disciplines such as AI (Artificial Intelligence) are capable of transforming this raw data into information.

AI learns from the data and is used in a transversal way in areas such as medicine, marketing, electricity demand prediction, purchase recommendations or the assignment of the most efficient transport routes, and more.

Cybercrime can cause devastating effects in terms of financial losses, affecting companies and individuals. A recent report by Juniper Research estimates that the cost of attacks resulting in a security breach averages nearly $4 million in the United States and that the cost to the global economy is about $400 billion. It is estimated that in 2024 this cost will reach $3 trillion, with an average annual growth of 11%.

Cybersecurity is a set of technologies and processes designed to protect computers, networks, programs and data from attacks, damage or unauthorized access. Traditional tools such as anti-virus, firewalls, access control and cryptography may not be enough, considering the current needs of the industry. Although all these techniques continue to work, they require in most cases a lot of manual work, taking into account the changing cyberspace, where every day there are new security threats.

By contrast,  Data Science is providing the necessary change to improve these operations. Machine Learning algorithms can be used to learn or extract information from data or find patterns of security incidents and prevent them. For example, automatically detecting malware or a suspicious trend, alerting the cybersecurity operator and reacting in seconds.

How cybersecurity leaders are overcoming the new risk landscape

We live in the age of data and data-based decision making. Data Science has emerged in recent years as a new field of science focused on understanding data. There is still much debate about big data and Data Science, but what everyone seems to agree on is that Data Science has emerged as a new interdisciplinary and cross-cutting field, with disciplines such as statistics, Artificial Intelligence, computing but also business management.

Cybersecurity is a set of technologies and processes designed to protect computers, networks, programs and data from attacks, damage or unauthorized access.

many researchers use the term Data Science to describe the interdisciplinary field that synthesizes and is based on statistics, computer science, Machine Learning, computing, communication, management and sociology to study data and their environments. In this way data can be transformed into knowledge and this allows for better decision making.

Based on the great analytical capacity of Data Science, including Machine Learning techniques, it is possible to provide a competitive advantage to traditional Cyber Security techniques. Being able to understand the problems, collect the security data from different sources, prepare the data to feed the models, build and update the data based models, in short provide intelligent security services.

Generally in the field of cybersecurity, traditional techniques were used to detect threats, such as file hashes, custom written rules such as signatures, or other traditional security techniques. But if we think of cybersecurity as a “large data provider”, Data Science can be applied to accelerate the analysis, detection and prevention of threats. This is where the concept of Cyber Security Data Science comes from.

The concept of Cyber Security Data Science incorporates the methodology and techniques of Data Science and Machine Learning as well as the analysis of the behavior of different security incidents. This concept refers to collecting a large amount of data from many different sources, analyzing the information using Machine Learning technologies to detect security risks and/or attacks by discovering useful information or obtaining patterns based on data.

It does not mean that with these technologies we will not need security experts, but once again, Artificial Intelligence with a focus on Machine Learning will help provide what we call “augmented intelligence”. Cyber Security Data Science has the capacity to provide security analysts with a tool to make their work more effective and faster.

Cyber Security Data Science has the capacity to provide security analysts with a tool to make their work more effective and faster.

Currently, most companies with cybersecurity products already incorporate Data Science techniques. Likewise, new opportunities are opening up for security analysts and experts in Data Science or Machine Learning to work together. Currently in Spain, the recent report EPyCE 2019 prepared by the Spanish Association of HR Directors and the collaboration of several consulting firms, shows the data scientist and the security expert among the most demanded professions.