Federated Cloud Services for Cross-Platform Data Integration

With the speed at which internet technology is developing, there is increasing worry about user alignment across online social network platforms (OSNPs). Customers tend to register numerous accounts across various OSNPs, while networking platform are reluctant to share user data and network makeup due to privacy concerns and corporate motives. These factors make cross-platform user alignment extremely difficult. Given this, we suggest a social network alignment (HESNA) algorithm that is based on homomorphic encryption and considers privacy leaks. To be more precise, we first view the OSNPs as a system made up of several social networks, in which each member owns a distinct private sub-network within the system. Subsequently, two external servers employ the HE approach to securely encrypt, combine, and decrypt the alignment data, thereby safeguarding the privacy information of sub-networks. Ultimately, user alignment is accomplished by each sub-network using the combined alignment data that was returned from the external server. According to the research results, the HE-SNA approach could protect individuals' privacy sub-networks while providing independent servers with a collection of local constructed models. Additionally, the HE-SNA obtains a more prospective network aligning effectiveness rather than merely employing its architectural information as well as alignments data since it protects the topographic structure data of a single private sub-network.