In the end, Data Science allows the cybersecurity sector to move from the assumption to the facts. During the last decade, the cybersecurity sector has been worried about FUD: fear, insecurity and doubts. Consumption in cybersecurity was based on the argument that “if we do not have an XYZ chart, then we just have to blame it when the bad happens”.
And bad things get bigger. The relationship between the industry and cybercriminals is asymmetric: the attacks are successful due to the challenge that companies face to maintain complete cyber hygiene: there are tens of thousands of computers and thousands of employees have these computers. And just as in the fight against terrorism, the opponent must only succeed once, while the defenders must always do so.
This is further complicated by the numerous information systems and security technologies that have been used to protect society in recent years. They often do not talk to each other, and those who are responsible for security, understandably difficult to see the combined image of what is happening.
However, this blind and justified spending time for the FUD station is old. The main information security officers do not want to work by instinct, they want and should be able to develop a value proposition that determines how to prioritize, where to focus, justify it and then show how it can be resolved in a way that can be understood. It is based on this to have access to the correct information.
That’s where the data is put. With relevant data, CISO can translate technical risk into commercial risk, give a commercial case to resolve it and demonstrate success. The current struggle is that CISO has information that is sensible, but not timely, either timely, but not sensible because the content is too technical and is silenced. What they really need are data that allows them to market and measure a security program; these are key gaps in cybersecurity that must be closed.
CISO wants to effectively market a security program to demonstrate the state of risk and priorities, so that it can reveal opportunities, demonstrate success and identify the board of directors, where they will get the best payment step in the calendar. The key areas of cybersecurity are an identification (or prevention), detection, response and recovery. There is already a large number of expenses and investments in data access in the areas of detection and response, but in the end, no organization is currently more secure.
This is because the main cause is often a failure in prevention, which requires improvements in corporate cyber hygiene. It is obvious that it has been violated, but prevention is better than medicine. New data approaches are approaching.
Many large organizations already have a team of data scientists, but generally, do not work in the field of security. Report to the Data Director and deal exclusively with commercial results. For those companies that are beginning to deal with data on data science as part of their security strategy, they mostly come from outside consultants.
With the security team, data science can be integrated with the controls, helping them to better understand how to focus and can help manage up by combining technical data to “measure something that is important” and ensure that data is robust and not deceptive (by mistake or otherwise).
At the crossroads of data science, large data technology and cybersecurity, there are great opportunities that will allow companies to gain control of “cyber” as a business risk. Global banks are at the forefront of recruiting scientists for the security team and combining data in Hadoop environments.
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