Nozomi Networks has patented a method for automatically deriving attack paths in a network by defining the network’s enriched topology, identifying vulnerabilities, building an atomic attack database, and translating them into a formal model. The method uses deep packet inspection and active queries to enhance network information and assess vulnerabilities. GlobalData’s report on Nozomi Networks gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Nozomi Networks, Facial recognition AI was a key innovation area identified from patents. Nozomi Networks's grant share as of January 2024 was 12%. Grant share is based on the ratio of number of grants to total number of patents.
Automatic derivation of attack paths in a network
A recently granted patent (Publication Number: US11831671B2) discloses a method for automatically deriving attack paths in a network. The method involves defining the network's topology as an enriched network topology based on exchanged packets, identifying vulnerabilities as information artifacts, building an atomic attack database, translating the topology and vulnerabilities into a formal model, and using a Satisfiability Modulo Theories (SMT)-based model checker to find attack paths. The process includes deep packet inspection, active queries, vulnerability assessment, and creating atomic attacks based on system states. The SMT-based model checker operates in discrete time steps, defining a circuit with a global clock.
Furthermore, the patent details the components of the circuit-like formal model, including primary inputs, primary outputs, latches, gates, comparators, and constants. The primary inputs and outputs can be Boolean or integer types, while latches store initial values and are updated at each time step. Gates implement basic logic functions like AND, OR, NOT, and comparators handle arithmetic operations. The method ensures that the system's state is defined at each time step by creating latches for each node and feature, with values determining the system's state in subsequent time steps. This innovative approach to automatically deriving attack paths in a network showcases a comprehensive and systematic method that leverages formal models and SMT-based model checking to enhance network security and threat detection capabilities.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
