Recognition of Cyber-Intrusion patterns in user cognitive behavioural characteristics for remote identification

Cyber-attacks keep threatening global networks and information infrastructures. The threat is getting more and more destructive and hard to counter day by day as the global networks continue to enlarge exponentially with limited security counter-measures. As this fact requires more sophisticated methods and techniques in urgency, a multidisciplinary remote cognitive observation technique is proposed in this paper to meet today's cybersecurity needs. The proposed method introduces a non-traditional Cognitive Psychology and Artificial Intelligence (AI) based remote threat identification which can be considered during the cyber security system design. It also enables to access the cognitive behavioural parameters of an intruder/hacker remotely without any physical contact via online connection, disregarding the distance of the thread. The ultimate goal of this work is to develop a supplementary cognitive cyber security tool for next generations secure online banking, finance or trade systems.