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    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Centralized Versus Decentralized Digital Identity Architectures: Simulation Models of Data Exchange</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Yoshiaki Fukami</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Takumi Shimizu</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Teruaki Hayashi</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Hiroki Sakaji</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Hiroyasu Matsushima</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Keio University</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>The University of Tokyo</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Shiga University</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>yofukami@sfc.keio.ac.jp</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>takumis@sfc.keio.ac.jp</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>hayashi@sys.t.u-tokyo.ac.jp</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>sakaji@sys.t.u-tokyo.ac.jp</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>hiroyasu-matsushima@biwako.shiga-u.ac.jp</string-name>
        </contrib>
      </contrib-group>
      <fpage>94</fpage>
      <lpage>95</lpage>
      <abstract>
        <p>In order to utilize big data generated from distributed cloudbased services, a digital ID is required to link between data and its subjects. Decentralized Identifiers (DID) have been developed to manage data from various services with privacy protection. We analyzed two ID architectures, DID and centralized ID (CID), with simulation models to evaluate the efficiency of ID architectures. In a monopoly market where there is no competition between ID providers, there is no difference between DID and CID. However, if there are multiple ID providers without interoperability, service providers have access to more data in the DID architecture compared to CID. However, this result was affected by the design of the model without ID federation technologies. Currently, service providers can receive data from many third-party services with the ID federation standard. Also, the simulation results that DID is very efficient for data distribution should be carefully interpreted by considering the upcoming costs for implementation.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>Background</title>
      <p>In recent years, consumers have come to have a large
number of user accounts linked to more and more
cloudbased services. This has led to the accumulation of a wide
variety of attribute data in the cloud, increasing the potential
for the creation of new services, while at the same time
developing a means of sharing data that is fragmented
between services in a way that is easy to use and protects the
rights of consumers. Service providers can identify
consumers with digital IDs provided by third party
companies and obtain attribute data stored by other services
under consumer authentication.</p>
      <p>Most of the data accumulated from multiple services is
linked to the ID issued by a specific small number of
companies, and such companies also provide functions of
authorization. This means that there is some risk that
distributed data could be accumulated, analyzed and utilized
for unintended use under malicious intent. The risk of
privacy infringement is increased by aggregating various
attribute data. While the ID federation enhances consumer
convenience, it also increases the risk of privacy breaches.</p>
      <p>DID is an architecture in which the entity that provides
attribute information issues digital IDs in a distributed
manner enabled by blockchain technologies. In contrast to
DID, an architecture that uses existing ID federation
technology is called a Centralized Identifier (CID). With
DID, aggregated data can be utilized only with consumer's
___________________________________
In T. Kido, K. Takadama (Eds.), Proceedings of the AAAI 2022 Spring Symposium
“How Fair is Fair? Achieving Wellbeing AI”, Stanford University, Palo Alto, California,
USA, March 21–23, 2022. Copyright © 2022 for this paper by its authors. Use permitted
under Creative Commons License Attribution 4.0 International (CC BY 4.0).
authentication, and without linking to specific ID providers
such as Google and Facebook.</p>
      <p>From the service provider's point of view, it is
advantageous to be able to obtain and utilize diverse data at
low cost, and it will encourage the emergence of innovations
in the form of new services. Both architectures, CID and
DID, have their advantages and disadvantages, and it is
difficult to determine which is better simply. Therefore, we
use a simulation approach in order to study many factors in
an integrated manner.</p>
      <p>
        In multi-agent simulation, people and objects can be
represented as agents, and phenomena resulting from their
interactions can be observed. For example, it is applied to
fields such as traffic
        <xref ref-type="bibr" rid="ref1">(Bazzan &amp; Klügl, 2009)</xref>
        , pedestrian
flow
        <xref ref-type="bibr" rid="ref4">(Yamashita et al., 2014)</xref>
        , and market transactions
        <xref ref-type="bibr" rid="ref2 ref3">(Hirano et al., 2020; Yagi et al., 2020)</xref>
        . By confirming the
simulation results, it is possible to support decision-making
in planning and policy making related to them.
      </p>
    </sec>
    <sec id="sec-2">
      <title>Models</title>
      <p>This study employs simulation models to analyze the CID
and DID structures and their impacts on data exchange. In
the CID model, each user has some data which is managed
by ID providers. Service providers have their needs (i.e.,
which data a service provider needs to create products) and
try to obtain the data they need by accessing the IDs users
have. Verifiers may or may not get the data depending on an
ID that bridges transactions between users and verifiers. For
instance, if a verifier asks a user to share the data “a” and
the user uses the ID “A” for this transaction, the verifier can
get the data “a”. If the user uses the ID “B” in this case, the
verifier cannot get the data. In the DID model, there is no ID
provider in the transaction. A verifier directly contacts a user
and requests the data it needs. Each user decides whether
he/she accepts the request from a verifier. These models aim
to uncover the efficient data exchange structure considering
various parameters such as the number of users and CID
providers and the cost of transactions. Figure 1 describes the
model structures.</p>
    </sec>
    <sec id="sec-3">
      <title>Results</title>
      <p>We evaluate the models based on the number of data that a
service provider can access depending on the ID structures.
In the CID models, the key parameter is the number of CID
providers. If there is one CID provider, a service provider
can access all the user data via this particular CID provider.
Our simulation assumes 10,000 users in the model, so a
service provider can access 10,000 user data in this case. As
the number of CID providers increases, user data is
dispersed across CID providers and a service provider can
obtain only subsets of user data via a CID provider. In the
DID models, the key parameter is the attrition rate of service
provider’s data request. Since the DID requires users to
manage each transaction per data record by themselves
unlike the CID which allows CID providers to manage it, a
service provider sometimes cannot obtain the data due to
this burden of user’s data management. Figure 2 shows the
results of our simulation models considering various levels
of key parameters. As the graph indicates, the number of
data that a service provider can access dramatically
decreases as the number of CID providers increases. On the
other hand, the number of accessible data in the context of
DID stays relatively large even in the case of high attrition
rate.</p>
    </sec>
    <sec id="sec-4">
      <title>Discussion</title>
      <p>The result is that service providers have access to more data
in the DID architecture compared to CID. However, this
result was affected by the design of the model that only
introduced the authentication / authorization function of
independent third parties without ID federation technologies.
Currently, service providers are able to receive data from
many third-party services with the ID federation standard
such as OpenID connect.</p>
      <p>On the other hand, the simulation results show that
DID is very positive for data distribution. However, DID has
not been diffused yet, and it costs for both data providers
and acquirers to implement DID technology. The benefits of
DID architecture may be offset or negated by the costs of
dissemination, which are not reflected in this model.</p>
      <p>Future research needs more fine-grained models which
reflect real-world ID operations and practices being
developed at standard developing organizations and issues
mentioned above such as ID federation and cost structures
of ID architectures. This study opens up new research
avenues for digital identity structure and data exchange by
showing a basic understanding and implications of CID
versus DID architectures.</p>
    </sec>
    <sec id="sec-5">
      <title>Acknowledgments</title>
      <p>This work was supported by JSPS KAKENHI 19K23235,
20H02384, and 20K13599.</p>
    </sec>
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