B1165
Title: An honeypot-semantic approach of data acquisition and data mining for corporate compliance analysis
Authors: Vito Santarcangelo - iInformatica Srl (Italy) [presenting]
Massimiliano Giacalone - University of Naples - Federico II (Italy)
Diego Carmine Sinito - iInformatica Srl (Italy)
Abstract: A new interesting approach is shown for corporate distributed data acquisition thanks to the use of an innovative approach based on smart honeypot painting installed in corporate environments, smart honeypot plants installed in outdoor or manufacturing environments, with the support of an application survey. All the data acquired are certified thanks to the use of a blockchain. The concept of a honeypot is the best way to install the device for parameters monitoring in corporate environments without altering the characteristics of the work environment following the empathic design approach. Honeypots are designed in full compliance with confidentiality and GDPR compliance. Data acquired from honeypots and surveys are then processed by a data mining approach considering a specific semantic knowledge base related to the corporate context. This multivariate analysis is very useful for mapping the process gap of compliance, considering significant relations between variables. By following this approach, it is then possible to discover the KPI set of variables that have to be monitored for corporate compliance improvement. Some solutions are proposed for acquisition that can be useful to monitor the compliance of organizational models, and relative examples of multivariate analysis conducted by the use of a platform based on Weka environment.
