Cyber Influence of Human Behavior: Personal and National Security, Privacy, and Fraud Awareness to Prevent Harm

Abstract

The Internet and connected technology platforms have enabled an increase of cyber influence activity. These actions target a range of personal to national level security and privacy attributes related to cybercrime, behavior, and identities. These emerging threats call for new indicators for improved awareness, decisions, and action. This research proposes a cyber-physical-human spectrum of identification with a prototyped classification method. Classifier goals are to aid in awareness of activity and potential harmful intent such as detection of identity feature acquisition, fraudulent identities and entities, and targeting or influential behavior. Emerging malicious influence actors prey on human social demographic groups and trends using the Internet infrastructure with social network platform access to large target populations as their attack surface. The methodology discusses how this problem could benefit from a combined human-technical approach to understand indicators of influencing human perception that persuade someone perform a desired action. This method is designed to aid in rapid influence awareness and introduce a counter-influence concept. A prototyped experiment trial demonstrates how awareness may be beneficial to balancing national security with personal privacy.