Real-time analytics are a powerful tool for identifying denial of service attacks and other cyber threats, risks and events.
Prolexic recommends that the information gleaned from real-time data analytics is the best foundation for a DDoS mitigation strategy that supports root-cause analysis of how a denial of service attack could affect an Internet-facing network. Potential targets are application logins, system performance (latency), network systems and mission-critical applications.
Prolexic advises that DDoS mitigation providers and their customers can work more effectively by extracting intelligence from massive streams of data to determine the best response to the DDoS attack, resulting in faster mitigation and less risk of costly downtime.
“Today, every industry is deluged with data from multiple sources in different formats, and the business of cyber security and DDoS attack mitigation is no exception,” said Stuart Scholly, president of Prolexic. “Prolexic has learned that these “big data’ streams are valuable for DDoS mitigation only if data analytics are used to gain real-time insight into the trends, behaviors and events that make up today’s cyber-attack landscape. Most importantly, using real-time data analytics drives faster cyber threat identification and mitigation, and consequently helps Internet-facing organizations build a stronger cyber security strategy.”
Even the best automated data analytics systems cannot replace the experience of skilled DDoS and cyber threat mitigation technicians, who analyze and extrapolate the data to make meaningful conclusions.
The best data analytics strategy to support fast and effective DDoS mitigation is a combination of an automated data correlation and reasoning system, coupled with the human expertise of engineers and technicians with front-line success in fighting and defeating DDoS attackers.