(untitled) (International Journal of Engineering and Computer Science, 2016)
Event processing is an approach of capturing and processing the data about events. The data may come from multiple origins in complex event processing systems and transmitted through multiple security authorities. Present event processing systems are failing in conserving the privacy constraints of incoming event streams in a sequence of eventually applied stream operations. This problem emerges in large-scale distributed applications like a logistic chain where event processing operators may be escalated over multitudinous security domains .This paper presents a frail access management in multi-hop event processing networks. Literally this paper offers a solution to maintain privacy constraints even when the events turn to correlated complex events. The obfuscation value calculated using Bayesian Network is used to decide whether inheritance of access requirement is needed. The implementation offers methods to enhance the obfuscation calculation and to increase the Bayesian Network size to measure obfuscation over multitudinous correlations that reinforces the event streams.