How Advanced Security Analytics can help combat ever-increasing cybersecurity threats

Despite the latest IT solutions and a heightened awareness of cybercrime, thousands of enterprises get hacked every year. All the SIEMS, firewalls, end-point solutions are seemingly useless when it comes to a determined cybercriminal. For an organization and its data, the only way to stay ahead of the cybercriminals is by detecting and neutralizing them in real-time. This is where Advanced Security Analytics for enterprises make a real difference.

Role of Big Data Analytics in Security

Advanced Security Analytics for businesses leverages the latest AI and ML technologies to find, identify, and eliminate threats in real-time. They use continuous, real-time threat analysis to generate security alerts with contextual data to find real cyber threats from a mountain of data, thus reducing the problem of false negatives most systems are hobbled by.

Big data analytics not only neutralizes external threats but also monitors for insider threats, identifying risky behaviors against baseline figures and dealing with them via automated workflows.

Core components of Advanced Security Analytics

1.      Unifying data streams and enriching them

Organizations deal with a veritable mountain of data - This includes raw network traffic, raw packet-capture, end-point data, VPN, Proxy, firewall logs, SIEM data, structured data, or log files. All this data is ingested, enriched, and analyzed in real-time by adding a layer of contextual information such as geo-IP location, geo-coordinate specifics, IP vs. threat-intel-feeds, the reputation of that particular IP, and more.

2.      Identifying Threats in Real-time

Data enriched during the first stage is fed into a real-time stream-processing engine set up across a multitude of machines. This stage of Advanced Security Analytics comprises a “known threats” rules engine, which flags perceived threats. These unique query engines process and store information in real-time (in Elastic Search and Hadoop). All this is used for identifying and analyzing any anomalies that might point towards a problem.

3.      Automating solutions

The final step of the solution for Advanced Security Analytics for businesses provides automated workflows for each type of threat or anomaly. The amount of data and network traffic in current business scenarios is made for automated cybersecurity control as it keeps the whole system completely secure in real-time with minimal human intervention.