The integration of information retrieved from mobile devices, social media and several type of sensors, suggests to exploit the online analysis of a large amount of data allowing to detect and identify dangerous events.
Such online approach enables the detection of critical situations as soon as they happen, so that a corresponding reaction can be successfully performed. Many application domains can benefit from this kind of analysis such as surveillance and protection of critical infrastructures and areas, for example: train stations, airports, public squares, world heritage protected areas in some cities of art and so on.
The process, starting from the data extraction, leads to the detection of the situation in progress. It introduces several challenges:
- first of all, it should be highly efficient in order to handle a huge amount of data and detect the situation in progress before it is too late to perform the reaction successfully;
- it should be also tolerant to different types of noise, meaning that the process should acknowledge only trusted information from trusted sources, otherwise it could lead to wrong scenario definitions and consequently wrong decisions;
- it should be sufficiently reliable to trust the logged events, including architecture resilience and trustworthy data collection.
Complex Event Processing (CEP) systems are widely applied to manage streams of data, in different fields and applications, as business process management, financial services, and also security monitoring, especially for complex, large scale systems where large amounts of information is generated.
The Secure! Project exactly locates in such an application scenario. The project has studied and developed a service oriented infrastructure which, by resorting at diverse technological tools based on image forensics, source reputation analysis, Twitter message trend analysis, web source retrieval and crawling, and so on, provides an integrated event assessment especially regarding crisis management.
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