This paper propose a novel method for obtaining statistical results such as averages, variances, and correlations without leaking any raw data values from data-holders by using multiple pseudonyms. At present, to obtain statistical results using a large amount of data, we need to collect all data in the same storage device. However, gathering real-world data that were generated by different people is not easy because they often contain private information. The authors split the roles of servers into publishing pseudonyms and collecting answers. Splitting these roles, different entities can more easily join as pseudonym servers than in previous secure multi-party computation methods and there is less chance of collusion between servers. Thus, our method enables data holders to protect themselves against malicious attacks from data users. We also estimated a typical problem that occurred with our method and added a pseudonym availability confirmation protocol to prevent the problem. We report our evaluation of the effectiveness of our method through implementation and experimentation and discuss how we incorporated the WebSocket protocol and MySQL Memoty Storage Engine to remove the bottleneck and improve the implementation style. Finally, we explain how our method can obtain averages, variances, and correlation from 5000 data holders within 50 seconds.

We have developed an active Q adaptor (AQA) to achieve integration of multiple management protocols and dynamic modification of managed object (MO) definitions. To achieve dynamic modification, we introduce a new MO framework, called dynamic-MO, which has the ability of modifying its own definition. A dynamic-MO is composed of meta-data and some behavior programs. Meta-data lists attributes of a dynamic-MO in a text format and a behavior program describes actions of a dynamic-MO in scripting language such as Java, Tcl, etc. In our AQA architecture, modules which manage individual components of a dynamic-MO communicate among themselves via an object request broker (ORB) in order to achieve system scalability with high performance. To realize the functionality of a dynamic-MO, we propose interfaces among these modules that are independent of dynamic-MO definitions and an update mechanism of behavior programs. We define the interfaces based on the common management information protocol (CMIP) operations to avoid re-defining the interfaces when dynamic-MO definitions are modified. Furthermore, to execute modified behavior programs without any negative influence on the workings of the other behavior programs, we employ a Java class-loader which has its own specific naming-space on a Java virtual machine (Java VM). With all of these features, our AQA is extremely promising for developing programmable network management systems for end-to-end management of heterogeneous telecommunication networks.