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Consider the possibilities of a technology that learns your dynamic environment and responds to threats in near real-time. Through a partnership with NVIDIA, a leader in visual computing, Booz Allen Hamilton offers just that—a managed service that easily integrates with existing network solutions and delivers sophisticated network defense.
Cyber attacks are impacting daily life and attackers are getting more creative.
In a rapidly-transforming cyber threat landscape, network defense solutions must be innovative and flexible to protect against new attack tactics. While current signature detection techniques combat known attack structures, they're reactive. The response to an attack typically takes weeks, and sometimes it stretches into months. These challenges are compounded by the individualized nature of the network—each demands a system that understands its unique threats.
Cybersecurity experts must now build an adaptable solution that learns the norms of a network, while rapidly evolving in defense of new attack structures. While experts can innovatively adapt and learn malicious network anomalies, they've tried using artificial intelligence (AI) and machine learning-driven computer models without much success. A major reason is that cybersecurity experts used to complete model training offline, using stagnant and segmented data. They discovered the AI models took a long time to build and worked best with predictable behavior, similar to traditional signature-driven defense.
“Cyber attacks are continuously evolving and becoming more sophisticated. To protect a network, defenses must be adaptable, intelligent, and customized to that specific environment. ”
- Joshua Patterson, NVIDIA's director of applied solutions engineering
Booz Allen fuses innovative technology with pioneering data science techniques.
With recent advancements in graphics processing unit (GPU) technology driven by our partner NVIDIA, Booz Allen moves network defense from reactive techniques to machine intelligence approaches. These pioneering solutions learn both the threat—for example, analyzing threat feeds such as Cyber4Sight by Booz Allen—and the environment simultaneously. This allows us to develop models from “data-in-motion,” which respond to new and emerging threats.
With the best technology on the market, we fully analyze all aspects of network packets in near real-time for greater insight, without the risk of dropped data. Building from a foundation of more detailed data, our suite of machine learning models can detect distributional traffic shifts, anomalous patterns of network behavior, and creative attacks as they originate.
We layer multiple techniques, from neural networks—computer systems based on neurons in the brain—and Bayesian statistical models to construct the most comprehensive cyber-alerting solution available. It's tuned and optimized for each network implementation. Using a machine-intelligent feedback loop, we also move discovered insights back through our models to mature each modeling component and the overarching analytical structure. The result is an optimal network defense solution.