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American University jettisons signatures and open-source tools for network detection and response
Technology Category
- Analytics & Modeling - Machine Learning
- Cybersecurity & Privacy - Network Security
- Networks & Connectivity - Network Management & Analysis Software
Applicable Industries
- Education
Applicable Functions
- Business Operation
Use Cases
- Cybersecurity
Services
- Data Science Services
- System Integration
The Challenge
American University, a private institution in Washington D.C., was preparing to expand its cloud presence and needed to enhance its cybersecurity measures to protect its public cloud, data center, and campus networks. The university was facing two significant cybersecurity challenges that were consuming a significant amount of time and resources. The first was the use of open-source tools to monitor network traffic, and the second was the use of signatures to detect intrusions. The university's network supports about 60,000 users with more than 20,000 devices at any given time, along with 700 servers and hundreds of applications. The information security team was looking for non-open-source solutions that utilized artificial intelligence and aligned with their goals.
About The Customer
American University is a private institution located in Washington D.C. The university supports a network of about 60,000 users with more than 20,000 devices at any given time. It also supports 700 servers and hundreds of applications. The university was preparing to expand its cloud presence and needed to enhance its cybersecurity measures to protect its public cloud, data center, and campus networks. The university was using open-source tools to monitor network traffic and signatures to detect intrusions, both of which were consuming a significant amount of time and resources.
The Solution
After evaluating various vendors, American University chose the Cognito® Network Detection and Response (NDR) platform from Vectra®. The Cognito NDR platform uses AI-derived machine learning algorithms to automatically detect, prioritize, and respond to in-progress attack behaviors that pose the highest business risk across cloud, data center, IT, and IoT networks. The university deployed Vectra virtual sensors on every VMware server to monitor all traffic between servers. The Cognito NDR platform automated manual Tier-1 and Tier-2 security tasks, reducing the security analyst’s workload and allowing them more time to focus on incident investigations and threat hunting. The platform also integrates and shares context and insights with third-party security solutions for end-to-end threat management and visibility.
Operational Impact
Quantitative Benefit
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