About 35% of cyberattacks go unnoticed, according to the study Big Data and Predictive Analytics: On the Cybersecurity Frontline, promoted by IDC and sponsored by SAS. The finding demonstrates that organizations need to take a proactive stance to understand threats before the 'attacker' causes any kind of damage. This requires constant monitoring of network behavior so that irregular activity can be distinguished from normal activity.
For this change to take place, companies need a new set of security solutions to deal with the increasing sophistication of attacks. By applying predictive and behavioral analytics to all available enterprise data, you can estimate threat potential, detect potential attacks, and achieve advanced intelligence. These analyzes need to be performed in real time so that threats are proactively minimized before a significant loss occurs.
According to Stu Bradley, senior director of fraud prevention practice at SAS, network security can be the most critical area in organizations. “Big Data becomes a barrier for them to understand the true threat landscape. However, if optimized, the sheer volume of data offers significant opportunities to contextualize more accurate and faster threat detection,” he says.
Alan Webber, research director at IDC, said that after a thorough research of the challenges and gaps in the market, it was realized that companies need to be more strategic about network threats, enhancing their existing security systems with advanced behavior analysis. "Software vendors that have integrated the Analytics for Big Data platform at their core are well positioned to provide the market with an additional layer of security and detention."
IDC interviewed Information Security executives, users and industry experts in three industries: Federal Government, Financial Services and Energy. The objective was to learn about the evolution of the Cybersecurity landscape and understand how Big Data and predictive analytics can be deployed to address threats and risks faced daily.
The research explains that effective Big Data solutions must differ from reactive “gather and analyze” methods. Today, technologies exist for using data with deadlines and in ways that were not possible in the past. To gain value from Big Data, companies need behavioral analytics and tools like Hadoop to improve security at a faster pace.
Industry implications and opportunities
For the Government, maintaining the security of its data on a daily basis is crucial. US-CERT (United States Computer Readiness Emergency Team) recorded more than 46,000 incidents at US Federal Government agencies in 2013. IDC estimates that these agencies will spend more than U1TP3Q14. 5 billion in Cybersecurity to prevent attacks and identify incidents. In addition to multi-layered security defenses, government agencies have highly complex infrastructures made up of an extensive amount of technologies from older cloud and mobile application structuring systems. By turning to predictive behavior analytics, these agencies can shift their stance toward more proactive advocacy.
In the Utilities and Energy industry, IDC research found that advanced and predictive analytics are critical in advancing the cyber order, including regulatory compliance. Companies are just beginning to identify threats and realize the solutions available for big data analysis.
When it comes to Financial Services, Cybersecurity strategies remain at the forefront of discussions. IDC research predicted that the financial sector will spend over US$ 40 billion on operational risk management and cyber threats in 2015. It was concluded that US$ 27.4 billion would be spent on IT, information security, and frauds. With the shrinking gaps and complexity of digital channels, advanced analytics solutions and services have become key technologies for risk managers, data managers and executives.
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