Exprivia Solutions

Aerospace & Defence

Cyber intelligence: strategic decisions and investigational processes
Big Data Intelligence for Threat Prevention & Investigation
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Exprivia has a great deal of experience in developing solutions based on the use of advanced Data & Text Mining and Big Data Analytics methods for supporting strategic decisions, intelligence and investigation activities and, more in general, the processing/correlation of data coming from heterogeneous sources. The current developments are based on Cloudera, Solr, DeepKnowledge and are dedicated to intelligence for command and control systems designed to identify and prevent threats, correlating data coming from various sources (radar, OSINT, weather, reports, staff and vehicle databases, etc.).

Information Management & Big Data Intelligence
The DSS (Decision Support System) in managing emergencies includes:

  • correlation of events and information coming from heterogeneous sources (SIGINT Signals Intelligence, OSINT Open Source Intelligence, HUMINT Human Intelligence); 
  • monitoring and alerting: generation, aggregation and validation (elimination of redundancies) of alarms coming from multiple sources through the recognition of anomalous patterns; 
  • georeferencing of the information (integration with GIS systems); 
  • profiling of entities (people, companies, etc.) on the basis of behaviour (analysis of logs, mail, social networks, webs, etc.); 
  • identification of the actions necessary to resolve an emergency on a regulatory, statistical and contextual base. 

The Big Data Intelligence for Threat Prevention & Investigation functions
Based on Exprivia Big Knowledge technology, the system expresses the following main functions:

  • memorizing of knowledge (Knowledge HUB): resources to be protected (sites, projects, staff, etc.), potential threats (groups, people, etc.) organized by the type, events of interest, sources of information, etc.; 
  • management of heterogeneous information for structuring (databases, web pages, files, email, social networks) on the basis of a common logical structure; 
  • ability to process and correlate structured and unstructured data sources; 
  • single point of access to the information and derivable knowledge (internal alarm system); 
  • analysis of "unknown" or "strongly dynamic" cognitive domains (knowledge discovery and extraction via weakly supervised machine learning); 
  • analysis of "known" or "static" cognitive domains (knowledge extraction via strongly supervised machine learning); 
  • search by concepts (via natural language), classification of information, geo-referencing, extraction of entities (places, people's names, companies, etc.) all language independent; 
  • application of visual analytics methods supporting the analysis of complex events. 

Meta-SIEM platform
The platform includes intelligence capabilities on internal data and information, and OSINT. It offers advanced search functions (single access point), has the ability to aggregate and validate alarms coming from multiple sources (elimination of redundancies), includes the ability to georeference structured/unstructured data and is interoperable with market and open-source GIS systems using the OCG standard.