A Secure Group Collaboration Protocol for Nonverbal Human Social Signals Featuring Deception Detection

Abstract

Non-verbal human social signals have emerged as an important area of study including the analysis of human deception. The ability to credibly detect truth and deception can be critical today especially due to the wave of terrorism acts and illegal immigration upheavals just to mention a few instances where individuals might not be forthright with their information. Unlike for non-verbal human social signals, with other regular data many networked groups are collaboratively sharing data in order to achieve broader and more comprehensive results. To overcome the inherent danger of data exposure in groups with potential semi-honest participants, measures have been introduced to ensure privacy, integrity, and security in such collaborative exchanges. We do notice, however, that sharing of non-verbal human social signals data is lagging behind in such sharing. As this form of data is growing rapidly and prominently, we propose a protocol that extends group sharing of such data featuring human deception detection social signals among collaborative partners. The protocol will provide privacy, integrity, and security of the data during these exchanges.