# A Secure CDM-Based Data Analysis Platform (SCAP) in Multi-Centered Distributed Setting
## 1 Introduction  
The importance of medical data has been emphasized over the past several decades, and numerous medical institutions around the world have built systems to accumulate medical records. Following this trend, electronic medical record (EMR) or electronic health record (EHR) systems have been actively adopted in local hospital networks [1, 2]. With the recent development of big data and artificial intelligence technologies, researchers are attempting to use large numbers of medical data for secondary purposes such as the research and development of patient-centered services. However, it is unreasonable to derive statistically meaningful results using only the accumulated data in a single hospital. To overcome this problem, studies have been proposed to analyze data collected from several medical institutions, including multi-center or multi-source datasets [3, 4]. However, despite the apparent advantages of multi-center datasets, the following practical problems occur: (1) Hospitals maintain medical data inside the local network boundary of the institution for management and security reasons. Because this setting allows resources to be distributed over the network, it is necessary to consolidate medical data [3, 5, 6]. (2) In general, hospitals have a database structure for storing medical data. Differences in data formats can be a stumbling block when merging and further analyzing medical data collected from institutions [7, 8, 9]. (3) Transmitting data from the hospital network without proper security can violate patient privacy [10]. (4) Even if medical data are transmitted through secure network channels among institutions, patients may not want personal information to be included in the transmission [11, 12, 13, 14]. To effectively analyze data collected from various hospitals, these issues should be resolved. In order to resolve these problems, there has been an increasing number of attempts to build a data-driven research infrastructure based on the Common Data Model (CDM). A Medical CDM is a standardized format of clinical or observational data that differs from hospital to hospital. Therefore, based on the same CDM format, investigators do not need to write multiple analysis procedures to analyze data from multiple hospitals [15]. Another advantage of CDM is that it makes it easier for the hospitals to share the same or similar infrastructure to store and analyze their data. Currently, many consortiums in each country develop platforms to support multi-institutional medical research based on the above characteristics [3; 16; 17]. Although these platforms have improved the research environment and convenience, proper security should be considered, as they process medical data including patients' personal information. General security requirements for medical information system design and operation are stated in ISO/IEC 27799:2016 [18]: \"information security policy\", \"organization of information security\", \"human resource security\", \"assert management\", \"access control\", \"cryptography\", \"physical and environmental security\", \"operational security\", \"communications security\", \"system acquisition\", \"development\", and \"maintenance\", \"supplier relationships\", \"information security incident management\", \"information security aspects of business continuity management\", and \"compliance\". From a technical point of view, these requirements ensure that only authorized users perform authorized operations, and the integrity of the results is satisfied. The most important techniques to achieve this are user authentication [19; 20] and digital signatures [21; 22]. These techniques are used as part of many modern security protocols. For example, transport layer security (TLS) [10] supports authentication between parties communicating with each other, data encryption, and integrity guarantee for communication security.