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By Susan Hoffman
Automated cybersecurity for big data is becoming popular with many organizations, because this automation has several benefits. According to Karin Shopen of Palo Alto Networks, “Automation levels the playing field, reduces the volume of threats, and allows for faster prevention of new and previously unknown threats.”
But can automated cybersecurity keep up with ever-evolving cyber threats? Kuman Saurabh of Chief Security Officer notes, “Solving the cybersecurity crisis can’t start with the assumption that humans should be automated out of the system – in fact, it should be quite the opposite.”
What Is Big Data?
Some organizations, such as Google, Amazon and LinkedIn collect a huge amount of data each day from sources inside and outside the company. For these companies, it is impossible for traditional data processing software to process the massive amount of information they receive.
Big data can be analyzed to provide C-level executives with the information they need to make data-driven decisions. However, processing huge amounts of data is time-consuming and requires considerable effort by company employees.
To handle the demands of big data, several products and languages are on the market today. For example, Apache created Hadoop, a type of open-source software capable of summarizing, querying and analyzing the big data it receives. According to Apache, there are other tools designed to work with Hadoop, such as Hive (software that aids reading, writing and managing large datasets) and Pig (a query language that permits parallel computation).
How Automated Cybersecurity Protects Big Data
Like other types of data, big data is a tempting target for hackers. Big data contains sensitive and personal information that could be sold for a profit.
The automation of cybersecurity has helped the problem of defending big data databases. Teradata and the Ponemon Institute point out that when automation is used properly, it can detect anomalous and malicious traffic in organizational networks.
Cybersecurity Challenges of Big Data Continue to Increase
Due to its size, big data is dispersed in cloud-based and on-site locations. This multi-location storage system presents more security problems because the data isn’t stored in one central location. In an August 2017 Silicon Angle article, writer R.D. Danes quoted Druva’s Chief Marketing Officer Matthew Morgan: “Data protection built specifically for the cloud doesn’t work for the business applications they leave on premise….Likewise, old methods for protecting data on premise are too stiff and monolithic for the cloud and distributed applications.”
As the volume of big data continues to grow, automated cybersecurity at operating system and cloud services levels must grow along with it. CSO writer Roger A. Grimes predicts the following changes in the cybersecurity market:
- The protective services of security event information monitoring, such as the aggregation of security events, the reporting of security events, and corrective actions, will get better over time.
- Operating system vendors will allow trusted, cloud-based third parties to securely configure an organization’s computers.
- More security configuration vendors and more security configuration options will be available in the future.
- Security configuration vendors will be able to respond to security threats more quickly.
Career Opportunities Likely to Grow in Automated Cybersecurity
There is already a shortage of skilled professionals in the cybersecurity field, according to Tom Davenport and Adnan Amjad of Deloitte Insights. While artificial intelligence (AI) and machine learning have helped to automate some cybersecurity tasks, the need for human experts to monitor threats, interpret data and convey insights will remain.
As the challenges of cybersecurity and big data increase, there will be a need for skilled professionals to handle these challenges.