Paper Title
Secure Aware and Privacy Preserving Techniques for Big Service Composition

Abstract
Generally, big services are defined as collection of web services which handle and deal with Big Data. A big service composition is performed to generate aggregated or composite big services. Due to increasing volume of data, it is more complex to composite big service. An Improved Big service composition was used for big service composition which represented the services and user needs as graphs which were matched using approximate graph matching based on functional graph summarization. In the functional graph summarization, t-test was used to rank the web services. Based on the ranked web services, big services are composed. In this paper, secure aware and privacy preserving improved big service composition is proposed to provide security and privacy policies for improved big service composition. Initially in this paper, the declassification policies based on cryptographic operations is introduced which maintain data confidentiality and integrity. In addition to this, a privacy rule model is created which minimize the information leakage by checking the composition plans complies with user preferences and privacy policies of web services involved in the composition plan. The privacy rule model consists of six tuples are scope of privacy rule, purpose, usage level, maximum time period, domain of privacy rule and visibility. These privacy rules are used by services and consumers to define the privacy features of their resources. These methods provide secure and privacy preserving policies for big service composition. Keywords - Big Services, Web Service Composition, Privacy Preserving, Declassification Policies, Secure And Privacy Aware Technique.