Entropy-Trust-Homology Operational Security (ETHOS)

Secure and semi-secure distributed networks rely on static security protocols and certificate authorities to attempt to assure trust between network participants. Trust is based on what others initially think of the participant and not on what the participant actually says or does. Trust should be based not only on initial impressions but also on subsequent participation in the network. KBSI proposes an Entropy-Trust-Homology Operational Security (ETHOS) method of securing trust based on the information that is exchanged between the different edges of the communication network. Trust entropy metrics would be developed based on the pattern of information entropy flow between edges and on usage behavior. The metrics would be updated by a hardware device residing at each edge. The hardware device would use graph-based data mining techniques to update the metrics and autonomically collaborate with other edges in a distributed manner. The distributed collaboration would result in a secure, verifiable network where trust is based on what the edges do rather than solely on who the edges say the are.