Paper Title
Privacy Preservation Techniques for Data Transmission on Social Distributed Environment

Cloud computing is revolutionizing many ecosystems by providing organizations with computing resources featuring easy deployment, connectivity, configuration, automation and scalability. Privacy as well as security is foremost challenging issue for the cloud users as well providers. In public cloud environment, users transfer their data to public cloud server and cannot control its remote data. Thus the significant problems in public cloud storage include high computation cost, confidentiality of the data, integrity, availability and authenticity. Thus information security is one of the major problems in social distributed environment. Privacy preserving in cloud environments includes two aspects: data processing security and data storage security. Data storage security covers the issues of guaranteeing user data privacy when the data is stored in data center. An optimal attribute based encryption (OABE) is proposed to resolve this in our work. The Attribute Based Encryption aims to strengthen the sensitive data confidentiality in public cloud storage. The key values are optimally selected with the help of Hybridization of Artificial Bee Colony (ABC) and Beetle Swarm Optimization algorithm (BSO) to enhance the ABE algorithm. Once the ABE process is done, the information will be updated to service provider by the helper user for each cluster. Here PFCM clustering algorithm is applied to users to cluster the similar users. The PFCM clustering removes the limitation present in the FCM and PCM. The performance of proposed approach is analyzed in terms of different metrics. This method is executed in the functioning platform of python. Keywords - Attribute Based Encryption, ABC, BSO, PFCM