Abstract
A con man trick appears in cyberspace as a deception around cloud services from the service provider. Con man resistant trust algorithm continuously monitors cloud service's performance to detect this con man behavior. A cloud service is identified as a con when a lapse in service performance repeats by an amount more than the consumer of this service can accept. Like the repetition, performance of a degraded amount is another service performance attribute affecting consumer satisfaction. The work presented in this paper includes performance degradation following various models. The algorithm's mathematical scheme tracks the performance degradation amount. This revision evaluates con behavior in proportion to the performance degradation. This proportional affect follows an exponential function. Three alternative exponential functions are evaluated. Each of these functions is applicable for specific cloud services. These functions are compared with each other and their properties effecting con resistant Trust are analyzed resulting in a set of principles. Also, the relationship between performance degradation amounts and con behavior detection speed are unlocked resulting in a principle. The result correctness and effectiveness of the principles.