Most networks are secured through firewalls supporting intrusion detection and packet analysis. Yet attackers are becoming smarter and craftier. "Today's bad actors are much more sophisticated and sometimes organized and sponsored like an enterprise," Mir says. "Proactively defending the network requires a much different approach and predictive analytics is one of them."
Predictive analytics enables security analytics platforms to recognize anomalous behavior from systems, devices and/or users. "This fills a much needed gap," Soldato says. "With NGFW (Next-Generation Firewall) and endpoint technology, predictive analytics ... proactively identifies potential outside or even zero-day threats by recognizing what a file should or should not do in terms of the way it behaves when it is downloaded and executed or even simply saved."
Insider threat risk mitigation and rapid detection of security breaches are more important than ever, and predictive analytics can provide clues that escape human observers. "Predictive analytics, along with NetFlow or sflow data, can help weigh the risk of devices on your network (including end users) and predict which are at highest risk," Toy says. The cost of a network breach is typically several million dollars, Toy notes. "The more quickly you can detect and correct the breach, the less cost and impact there will be to your company’s reputation."
Comparing network pricing structures becomes complicated when multiple technical alternatives are available. "Software defined networks (SDNs), when coupled with predictive analytics, can help simplify forecasting and adjust network costs," Mir says.
"Analytics platforms that have implemented predictive analytics can help forecast network costs because they have the ability to ingest and process large amounts of network data," Soldato says. Predictive analytics is a proactive forecasting technology with the platform allowing enterprises visibility of what network usage, performance and quality will look like months and even a few years into the future. "In turn, this helps the enterprise prepare and forecast for network upgrades, new devices and personnel," he notes
As a prerequisite for network cost prediction, it is necessary to build network allocation cost foundations that enable the attribution of cost, both capital expenditures (CapEx) and operating expenditures (OpEx), to specific technical services or end customer products, Noya notes. "This is a difficult process for converged operators where network elements support multiple products and services, but ultimately necessary to accurately understand the total cost of ownership for product and service," he says. The network inventory should also be matched with the procurement catalog to create a continuum between network designs, network capacity and expansion costs. "Network predictive capacity analytics are employed to understand forward-looking costs," Noya says.
The first step in deploying predictive analytics for any form of network optimization is collecting and organizing clearly defined historical evidence of past problems. "You must know what constitutes normal functioning to identify what is abnormal," says John Crupi, vice president and engineering system architect for Greenwave Systems, an internet of things (IoT) software developer. "A spike in performance issues may be normal depending on the nature of the network, or it may be an early indicator of serious issues to come," he explains.
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