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INDEVCO relies on Vectra for complete visibility and proactive threat detection
Technology Category
- Analytics & Modeling - Machine Learning
- Cybersecurity & Privacy - Network Security
Applicable Functions
- Business Operation
- Discrete Manufacturing
Use Cases
- Cybersecurity
- Predictive Maintenance
Services
- Data Science Services
- System Integration
The Challenge
INDEVCO, a multinational manufacturing and industrial consultancy group, was facing challenges in detecting internal threats, gaining visibility into their network, and maintaining network hygiene. They had an open-source security information and event management (SIEM) solution and an endpoint detection and response (EDR) solution, but these were not sufficient. The company needed a solution that could help them better protect data and keep their operations running smoothly across their 38 manufacturing plants and 38 commercial companies worldwide.
About The Customer
INDEVCO is a multinational manufacturing and industrial consultancy group founded in 1955. The company produces a wide portfolio of corrugated, paper, and plastic raw materials and packaging, jumbo tissue rolls, consumer and away-from-home disposables, renewable energy solutions, converting machinery, and CNC machined parts. They serve a wide array of industries in nearly 90 countries worldwide, motivated by a grounding principle of sustainable development underscoring their dedication to integrating environmental sustainability and social responsibility in their operations. With over 38 manufacturing plants and 38 commercial companies across the globe, INDEVCO needed a solution to help them better protect data and keep their operations running smoothly.
The Solution
INDEVCO chose Cognito, the AI-driven threat detection and response platform from Vectra, to develop a new security layer for their security operations center (SOC). The Cognito platform collects and stores the right network metadata and enriches it with unique security insights. Cognito Detect uses security enriched metadata and sophisticated machine learning techniques to detect and prioritize attacks in real time. It applies AI-derived machine learning algorithms to automatically detect and respond to in-progress cyberattack behaviors in cloud/SaaS, data center, IoT, and enterprise networks. The solution provides broad visibility into threat history and significantly reduces the chance that attackers can operate on the network long enough to accomplish their goals.
Operational Impact
Quantitative Benefit
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