A multi-agent model for security awareness driven by home user’s behaviours

Abstract

Computer users are limited to perform multitask operations and processing information. These limitations affect their decision and full attention on security tasks. The majority of cybercrimes and frauds including effective security decisions and practising security management are related to human factors even for experts. Information Security awareness and effective home user training depend on concrete information and accurate observation of user behaviours and their circumstances. Users’ awareness and consciousness about security threats and alternatives motivate them to take proper actions in a security situation. This research proposes a multi-agent model that provides security awareness based on users’ behaviours in interaction with home computer. Machine learning is utilized by this model to profile users based on their activities in a cloud infrastructure. Machine learning improves intelligent agent accuracy and cloud computing makes it flexible, scalable and enhances performance.