Using readily accessible platforms and low-cost hardware, vendors can now create big data applications to process, store, and analyze vast volumes of unstructured data in real-time.
FREMONT, CA: Analytics is a central factor in the use of cyber resilience. With more sophisticated and ongoing threats and the clear fact that any entity must defend itself from all sorts of attacks, while the attacker wants only one successful attempt, organizations must rethink their data security principles. They need to shift beyond pure deterrence into the PDR paradigm: Prevent–Detect–Respond.
How Big Data Analytics Fits In
Improved detection is at the center of this strategy, and that is where big data processing comes into play. Detection must recognize evolving patterns of use; conduct complex analysis efficiently, close to real-time; to perform complex correlations through a range of data points, ranging from server and device logs to network incidents and user behaviors.
This aspect needs sophisticated analytics beyond simple rule-based methods and the ability to perform analysis on vast volumes of current and historical data, big data security analytics. Combining the latest state of research with security lets companies strengthen their cyber resilience.
Big Data Security Analytics: a New Generation of Security Tools
As the technology industry responds to these threats, a new wave of security analytics tools has evolved in recent years, capable of capturing, saving, and processing massive volumes of security data across the entire enterprise in real-time. Enhanced by additional background data and external threat information, these data are then processed using different correlation algorithms to find anomalies and thereby identify potentially malicious activities.
Unlike conventional SIEM solutions, these tools run in near-real-time and produce a limited number of safety warnings depending on the danger model. These alerts are enriched with additional forensic information and can significantly simplify the task of the security researcher and allow the accelerated identification and prevention of cyber-attacks.
What Makes Big Data Security Analytics Probable
Big data processing is the most significant technological advancement that makes these solutions possible. The market has now reached the point that business intelligence algorithms for large-scale data mining, historically only open to large companies, have been commoditized. Using readily accessible platforms and low-cost hardware, vendors can now create big data applications to process, store, and analyze vast volumes of unstructured data in real-time.