Platform

In-Depth evaluation through AI for Graphs

Muscope|Risk’s use of Deep Learning for Graphs represents a significant advancement in the field of cybersecurity. By leveraging this technology, we provide a deeper, more comprehensive analysis of data, allowing organizations to anticipate and respond to threats more effectively. As we continue to expand our graph coverage across Europe, our platform will become even more powerful, offering broader insights and stronger defenses for companies navigating the complexities of the digital age. Here details of how we do it:

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Muscope|Risk data structure

  • Information represented as a Graph: our platform organizes data in the form of graphs, where each node represents a company asset, and edges signify connections between these assets. This graphical representation allows for a detailed and holistic view of an organization’s entire ecosystem, capturing the intricate web of relationships and dependencies among various components.
  • Company assets interconnected: company assets are not isolated; they are interconnected with other entities, including providers and partners. By mapping these connections, Muscope|Risk creates a dynamic and constantly updated picture of the organizational structure, helping to identify potential vulnerabilities and interdependencies that might otherwise go unnoticed.

Technology and analysis

The primary benefit of our AI-driven graph analysis is its ability to anticipate threats and dangers effectively. By simulating various attack and defense scenarios, Muscope|Risk helps SMEs understand their vulnerabilities and strengths. This proactive approach ensures that companies are better prepared to defend against cyber threats, reducing the likelihood of successful attacks and minimizing potential damage.