Information and business data are among the most valuable assets of any company. Entrepreneurs are increasingly cognizant of the importance of this data for their success in the current market economy. Â
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Knowing this, we need to understand how to protect this information. Big data analytics professionals are making use of ​preventative technologies, as well as managed detection and response services​. Companies use these to deal with the constantly evolving, sophisticated cyberthreats caused by the increased amounts of data being generated on a daily basis.Â
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Technological innovation has taken the economy by storm, and every progressive business must embrace it in order to survive the cutthroat capitalist market economy of the 21st century. With mobile devices, tablets and wearable technology collecting vast amounts of data about their users, privacy and security have undoubtedly become primary concerns. Â
The role of big data and analytics in cybersecurity
The use of big data analytics and machine learning enables a business to do a deep analysis of the information collected. Ultimately, this gives hints of a potential threat to the integrity of the company. A business can create baselines based on statistical data that highlight what is normal and what is not. Â
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With such analysis, entrepreneurs and business managers can know when there is a deviation from the norm using the data collected. New statistical and predictive models and possibilities can also be created using this historical data by the use of artificial intelligence and machine learning. Â
Employee activity monitoringÂ
It is invaluable for any company or business organization to use an employee system monitoring program that relies on big data analytics. From there, the company’s compliance officer or the human resource manager can replay the behavioral characteristics of an insider.Â
While security threats are imminent due to ​employee related breaches​, both small companies and big corporations can prevent the compromise of the integrity of their systems by employees. They must limit the access to sensitive information only to staff that are authorized to access it. Staffers may use their logins and other system applications to change data and view files that they are permitted to touch.Â
To prevent such a threat, the system administrator should liaise with the human resource department to give every employee different login details depending on their level of complexity of their job description and responsibility to the business.Â
Intrusion detection systemÂ
Firewalls, multi-factor authentication and data encryption are common big data security measures today. Â
One critical and more progressive precaution is the incorporation of an Intrusion Detection System (IDS). IDS offers an umbrella to the enterprise network as it monitors all the traffic on certain segments that may have malicious intent or traffic. Â
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Big data analytics becomes critical in the use of the IDS, as it provides all the necessary information required for the monitoring a company’s network. It is also important to comprehend business requirements in order to make an informed decision about deploying an IDS system. Â
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IDS should be utilized when conducting all systems that are accessed through the internet, plus those that are mission-critical to the business.
Combating cyber threats in the future
Machine learning and big data analytics will add value to both government agencies and business organizations in helping them combat cyberthreats. In the meantime, they must build defenses that can withstand increasingly sophisticated cyber attacks.
In addition, with the increasing number of cyber attacks coming from employees and other servers, advances in big data are more important than ever. We need to be vigilant on advances in this field, and how they can help protect our data.
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