<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.0 20120330//EN" "JATS-archivearticle1.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Risks of Loss of Personal Data in the Process of Sending and Printing Documents</article-title>
      </title-group>
      <contrib-group>
        <aff id="aff0">
          <label>0</label>
          <institution>IT Step University</institution>
          ,
          <addr-line>Lviv</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Khmelnytskyi National University</institution>
          ,
          <addr-line>Khmelnytskyi</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>University of Warmia and Mazury Olsztyn</institution>
          ,
          <country country="PL">Poland</country>
        </aff>
      </contrib-group>
      <fpage>0000</fpage>
      <lpage>0001</lpage>
      <abstract>
        <p>With the introduction of the General Data Protection Regulation, many companies were forced to make significant changes to their systems to meet the new requirements. General Data Protection Regulation is a regulation within the European Union legislation to protect the personal data of all people within the European Union and the European Economic Area. It also refers to the export of personal data outside the European Union and the European Economic Area. Problems of converting existing systems into conformity are analyzed, changing the use of storage systems in accordance with the standard. It has been shown that there are significant risks to the security of personal data during the printing process, including: unencrypted transmission of personal data over the network; unencrypted storage of personal data during the printing process on printers' servers or hard disks; outputting confidential documents to the wrong printers; Documents containing personal data are released to third parties from the printer. It follows that critical equipment is network printers, which transfer sensitive data to which is carried out through the corporate network. A network printer also poses a security risk. It is advisable to use a print server to centralize print processes. Not only does this simplify administration, but it also enables security technologies to be implemented. However, the applications themselves are on a dedicated server or in the cloud. The connection from a print server to a network printer can only be protected by third-party solutions. This results in a high administrative burden, as the decisions of individual printer manufacturers must be installed and managed separately on the print server. Print data that is often sent unsafe to print servers and from there to network printers must be encrypted. Certificates that require a username and password should be used for this. This paper analyzes the risks of personal data being lost in the process of sending and printing documents related to the implementation in the European Union countries of the General Data Protection Regulation.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>Keywords: personal data, data storage systems, risks of personal data loss.
1</p>
    </sec>
    <sec id="sec-2">
      <title>Introduction</title>
      <p>
        The recently implemented General Data Protection Regulation is forcing many
companies to make significant changes to their systems to meet new requirements. As
Ukraine has an Association Agreement with the European Union (EU) since 2014,
Ukrainian printing companies must be ready for such changes in order to be able to
cooperate with European companies or provide services to foreign customers. In May
2018, a new General Regulation on Personal Data Protection (GDPR) of personal data
of users, was introduced. Given this regulation, the existing data transmission
processes, their processing within the information technology should be checked and all
security deficiencies should be eliminated [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ].
      </p>
      <p>This Regulation also applies to the export of personal data outside the EU and the
EEA within the framework of European Union legislation on the protection of
personal data of all users within the European Union and the European Economic Area.
The introduction of new functionality, which must be performed in real time (for
example, synchronous recording of each user request) reduces the bandwidth of
systems by 20 times. New technical challenges are emerging that need to be addressed in
order to effectively achieve strict compliance with the General Data Protection
Regulation. Therefore, in order to comply with the General Data Protection Regulation, it
is necessary to make changes in the data processing and storage systems.</p>
      <p>The new legislation provides new definitions on data collection and processing and
raises a number of issues. What information is considered personal data? What
information technology processes should affect the security of personal data? How to start
restructuring information systems in accordance with the new requirements?</p>
      <p>Therefore, existing information technology processes, in particular printing
processes, should be tested for security, and any security deficiencies should be
identified, corrected, and optimized. Also, the methods of using storage systems should be
changed according to the GDPR standard, in particular the printing process, the
transition of the document through various stages from launch to the final product.</p>
      <p>
        The paper analyzes the problems of retrofitting existing systems following the law,
changing the methods of using storage systems following the GDPR standard, in
particular, the risks of personal data loss in the process of printing and transferring the
documents for printing, the passage of the document through various stages from
launch to the final product. The individual stages, existing risks, and weaknesses of
the process security are illustrated [
        <xref ref-type="bibr" rid="ref2 ref4">2, 4</xref>
        ].
2
      </p>
    </sec>
    <sec id="sec-3">
      <title>General analysis of GDPR</title>
      <p>
        The General Data Protection Regulation is set out in 99 articles describing its legal
requirements and 173 summaries that provide additional context and explanations to
these articles. The GDPR is an expansive set of regulations covering the entire
lifecycle of personal data [
        <xref ref-type="bibr" rid="ref1 ref3 ref4 ref5">1, 3-5</xref>
        ]. Thus, achieving compliance requires interoperability
with infrastructure components (including computing systems, networks and storage
systems) as well as operational components (processes, policies and personnel). For
analysis it is necessary to use articles describing the behavior of storage systems.
They fall into two broad categories: the rights of data subjects (i.e. the people whose
personal data were collected) and the responsibilities of data controllers (i.e.
companies that collect personal data).
      </p>
      <p>
        Table 1 shows the impact of the articles of the General Data Protection Regulation
on data storage systems, i.e. the requirements of the articles on the functions of
storage systems [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ].
      </p>
    </sec>
    <sec id="sec-4">
      <title>Designing systems according to requirements</title>
      <p>Based on the analysis of GDPR articles, it is possible to identify six key features that
a storage system must support in order to be compatible with the GDPR. And also, to
characterize deviations of systems in support of the basic functions necessary for
performance of regulations.
3.1</p>
      <sec id="sec-4-1">
        <title>Storage characteristics according to the GDPR standard</title>
        <p>
          Timely removal. According to the GDPR, personal data cannot be stored for an
indefinite period of time. Thus, the storage system must support the mechanisms of TTL
counters for personal data (the maximum period of time for which the data packet can
exist until its disappearance), and then automatically remove them from all internal
subsystems in a timely manner. The GDPR allows the TTL to be a static time or a
policy criterion that can be objectively assessed [
          <xref ref-type="bibr" rid="ref6">6</xref>
          ].
        </p>
        <p>Monitoring and logging. To demonstrate compliance, the storage system needs to
check both internal and external interactions. Thus, in a strict sense, all operations,
regardless of the path (e.g., read or write) or control path (say, changes to metadata or
access control), must be registered.</p>
        <p>Indexing with metadata. Storage systems must have interfaces for fast and efficient
access to data groups. For example, accessing all personal data that can be processed
for a specific purpose, or exporting all data that belongs to the user. In addition, you
need to be able to quickly retrieve and delete large amounts of data that meet the
criteria.</p>
        <p>Access control. As the GDPR aims to restrict access to personal data only to
authorized institutions, for established purposes, as well as for a predetermined period of
time, the storage system must maintain fine and dynamic access control.</p>
        <p>Encryption. The GDPR requires personal data to be encrypted in both storage and
transportation. Although anonymization can help reduce the amount and size of data
that needs to be encrypted, encryption is needed and is likely to degrade storage
performance.</p>
        <p>
          Data location management. Finally, the GDPR restricts the geographical locations
where personal data may be stored. This means that storage systems must be able to
find and control the physical location of data at all times [
          <xref ref-type="bibr" rid="ref7 ref8 ref9">7-9, 15</xref>
          ].
3.2
        </p>
      </sec>
      <sec id="sec-4-2">
        <title>Degrees of compliance</title>
        <p>
          Although the GDPR is clear in its high-level objectives, it is intentionally vague in its
technical specifications. For example, the GDPR requires that personal data not be
stored indefinitely and must be deleted after the expiration date. However, the
regulations do not specify how soon after the data expires, they will be deleted. Seconds,
hours or even days? The GDPR is silent on this, only mentioning that the data should
be deleted without undue delay. What does this mean for system developers? This is
that GDPR compliance should not be a fixed goal, but a spectrum. To do this,
consider the variance in two dimensions: response time and capabilities [
          <xref ref-type="bibr" rid="ref1 ref8">1, 8</xref>
          ].
        </p>
        <p>
          In real time against possible compliance. Real-time compliance is when the system
completes a GDPR task (for example, deletes expired data or responds to user
requests) synchronously, in real time. Otherwise, we classify tasks as those that need to
be performed later. Given the harsh sanctions for violating the law (up to 4% of total
revenue or € 20 million, whichever is higher), it would be advisable for companies to
delete the data as soon as possible. However, the requirement to meet the
requirements of the law in real time leads to significant overhead costs. This problem is
exacerbated for large organizations. For example, the Google cloud platform informs its
users that deleted data must be completely removed from all internal systems, but this
can take up to 6 months [
          <xref ref-type="bibr" rid="ref10 ref11 ref9">9-11</xref>
          ].
        </p>
        <p>Full and partial compliance. Systems that differ in response time demonstrate
different levels of detail and capability. These differences are due to the fact that many
of the requirements of the GDPR depend on the design principles and performance
guarantees of certain systems. For example, file systems do not implement indexing
to files as a basic operation, because this feature is usually supported by applications
such as grep. Similarly, many relational databases only partially and indirectly
support TTL, as this operation can be implemented using user-defined triggers that are
inefficient. Thus, we define full compliance in order to support all GDPR functions,
and partial compliance as supporting functions in combination with external
infrastructures or components.
4</p>
      </sec>
    </sec>
    <sec id="sec-5">
      <title>Characteristics of personal data protection</title>
      <p>
        According to the GDPR, individuals have the right of protection of their personal data
(Article 1, GDPR [
        <xref ref-type="bibr" rid="ref10">10, 15</xref>
        ]). However, the question arises as to how to recognize
whether certain data or information is considered personal data. Data falls into the
category of personal data when a person can be directly or indirectly identified, such
as by name, telephone number, account details, postal or IP address.
      </p>
      <p>Data processing is legal only if at least one of the following conditions is met
(Article 6 of the GDPR - Legality of processing):
• the data subject has consented to the processing of his or her personal data for one
or more special purposes;
• processing is necessary for the performance of the contract to which the data
subject is a party, or for taking action at the request of the data subject prior to the
conclusion of the contract;
• processing is necessary to comply with the statutory obligation that applies to the
controller;
• processing is necessary to protect the vital interests of the data subject or another
individual;
• elaboration is necessary for the performance of a task in the public interest or the
exercise of official authority vested in the controller;
• the processing of personal data is necessary for control, except when such interests
are outweighed by the interests of the fundamental rights and freedoms of the data
subject, which require the protection of personal data, especially if the data subject
is a child.</p>
      <p>
        The right to protection of personal data is protected by Art. 5 GDPR (Principles of
personal data processing) [
        <xref ref-type="bibr" rid="ref1 ref12">1, 12</xref>
        ]. By law, companies responsible for document
protection are required to report data leaks in a timely manner. In addition, violations of
data protection directives are subject to very high fines.
      </p>
      <p>By May 25, 2018, companies had to review their IT processes, as well as document
or even simplify them. Existing descriptions of IT processes, such as review
processes, may need to be adjusted or even updated. One of the elements of personal data
protection is the optimization of the complete printing process [13], as it often goes
unnoticed that there are significant security risks in the printing process (Fig. 1).
These include:</p>
      <p>R pr = R trans , R encrypt , Rincor , R third
where</p>
      <p>R trans - not encrypted transfer of personal data over the network;</p>
      <p>R encrypt - not encrypted storage of personal data during the printing process on
servers or printer hard drives;</p>
      <p>Rincor - output of confidential documents to incorrect (unprotected) printers;
R third - documents containing personal data are received by third parties from the
printer.</p>
      <p>The probability of losing personal data during printing will be the sum of the
corresponding probabilities</p>
      <p>p(R pr ) = p(R trans ) + p(R encrypt ) + p(Rincor ) + p(R third )</p>
      <sec id="sec-5-1">
        <title>Consider each element separately.</title>
        <p>The risk of network security is quite high due to the general trend of replacing printers
in the workplace with network printers. This is often used to optimize administrative
and financial costs. However, this results in the transmission of sensitive data over an
unsecured corporate network. If an attacker has access to network printer data, data
loss is guaranteed.</p>
        <p>The printing process begins in the application program. It runs either directly on
the corresponding workstation (Fig. 2), or on the remote desktop session host,
XenApp server [14-16] or virtual desktop (Fig. 3).</p>
        <p>
          XenApp - software for virtualization and delivery of applications from a remote
server to local devices of users through a thin client. In other words, this program
allows you to run Windows programs on computers and mobile devices running other
operating systems. In this case, the applications themselves are on a dedicated server
or in the cloud.
You can use a print server to centralize printing processes and reduce the risk of
losing personal data. This not only simplifies administration, but also makes it possible
to implement security technologies, as it allows to protect data with encryption using
application software [
          <xref ref-type="bibr" rid="ref8">8</xref>
          ]. In this case, the attacker needs to access a secure print
server, which makes it virtually impossible to lose data, or reduces it hundreds of times
[17].
Administrators protect programs and data through access protection, and encrypt
connections to servers and workstations. On the other hand, print data is often sent
unsecured to print servers and from there to network printers. This leads to the following
weaknesses:
• network cards of all devices covered by the print stream: workstation, desktop,
network switch, router, server and network printer;
• printers share access to the print server;
• access to network printer hard drives.
5
        </p>
      </sec>
    </sec>
    <sec id="sec-6">
      <title>Results of experimental studies</title>
      <sec id="sec-6-1">
        <title>Encryption during printing. There are several cases when the printing process needs to be optimized to achieve comprehensive and secure encryption of printing that meets the GDPR standard. From the program to the print server</title>
        <p>From the Server Message Block (SMB), the print data must be encrypted by a
printer-sharing program on a print server with Windows file sharing capabilities
(Fig. 2). This allows interoperability and access to shared printers on the print server
only through encrypted connections, which reduces the likelihood of losing
unencrypted data p(R encrypt ) .</p>
      </sec>
      <sec id="sec-6-2">
        <title>From print server to network printers</title>
        <p>Only third-party solutions can be used to connect from the print server to network
printers. The decisions of individual printer manufacturers increase the administrative
burden because they must be installed and managed for each printer user on the print
server and errors due to the output of data to other printers p(Rincor ) That is, you
need a universal, manufacturer-independent solution that is also compatible with a
large number of different structures and libraries.</p>
        <p>Network printer</p>
        <p>On the network printer itself, the risk of data loss by third parties p(R third ) is quite
high, so you need to make sure that unauthorized persons cannot enter the printer
interface. To do this, use certificates that require a username and password. If you are
using the printer's internal hard drive, it must be encrypted (on the hardware side).
Theft of ready-made printouts from the output tray can be prevented by user
authentication directly on the printer: smart card, smartphone, as well as PIN authentication.</p>
        <p>These probabilities can be specified only if the importance of data for attackers is
assessed (for example, bank details, patient medical data, ballots, etc.), but failure to
comply with GDPR recommendations with the appropriate activity of attackers is
likely to lead to their loss. The analysis showed that the use of encryption, even only
in some stages of network printing (Fig. 3) will significantly increase the security of
personal data.</p>
        <p>
          The table shows the average values of information risks, which should be used to
calculate the probability of data loss [
          <xref ref-type="bibr" rid="ref9">9</xref>
          ], Fig.4.
        </p>
        <p>Types of information risk
Mistakes of specialists when working with IT
Failures of technical means
Network equipment failures
Software failures
Malicious software
Spyware
Unauthorized access
Average rating, %
18
20
14
15
12
9
After analyzing the impact of articles (requirements) of the GDPR on data storage,
processing and transmission systems, we can conclude that achieving strict
compliance with the requirements is a difficult task. Attempting to strictly comply with all
regulatory requirements leads to a significant slowdown in systems. Therefore, to
better study this issue, it is necessary to conduct a detailed analysis of existing data
storage systems and analyze them according to the following parameters: efficient
logging, deleting, indexing metadata.</p>
        <p>As shown in this article, the printing process, which is an important element of the
system of storage, processing and transmission of data, goes through various stages
from launch to receipt of the final product. Therefore, the connection from the print
server to the network printer can only be protected by third-party solutions. This leads
to a high administrative burden, as the solutions of individual printer manufacturers
must be installed and managed separately on the print server, which provides a low
probability of data loss. A network printer also poses a security risk. When printing to
a network printer, it is not guaranteed that users' personal data will not be disclosed to
third parties. The paper proposes a reasonable scheme of the process of encrypting
print data at all stages from the program, through the print server to a network printer,
which minimizes losses and security of the data processing process.</p>
        <p>Acknowledgments. The authors are appreciative to colleagues for their support
and appropriate suggestions, which allowed them to improve the materials of the
article.
13. H. Zou, "Protection of Personal Information Security in the Age of Big Data," 2016 12th
International Conference on Computational Intelligence and Security (CIS), Wuxi, 2016,
pp. 586-589, DOI: 10.1109/CIS.2016.0142.
14. S. Cha and K. Yeh, "A Data-Driven Security Risk Assessment Scheme for Personal Data
Protection," in IEEE Access, vol. 6, pp. 50510-50517, 2018, DOI:
10.1109/ACCESS.2018.2868726.
15. M. Nazarkevych, I. Izonin, M. Gregus ml. and N. Lotoshynska, "An Approach towards the
Protection for Printed Documents by Means of Latent Elements with Fractal Grids and
Electronic Determination of Its Authenticity", Electronics, vol. 9, no. 4, p. 667, 2020. DOI:
10.3390/electronics9040667.
16. T. Kirkham, S. Winfield, S. Ravet and S. Kellomäki, "The Personal Data Store Approach
to Personal Data Security," in IEEE Security &amp; Privacy, vol. 11, no. 5, pp. 12-19,
Sept.Oct. 2013, DOI: 10.1109/MSP.2012.137.
17. L. Yuqing, "Research on Personal Information Security on Social Network in Big Data
Era," 2017 International Conference on Smart Grid and Electrical Automation (ICSGEA),
Changsha, 2017, pp. 676-678, DOI: 10.1109/ICSGEA.2017.91.</p>
      </sec>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          1.
          <article-title>Council of the European Union, "Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data</article-title>
          ,
          <source>and repealing Directive</source>
          <volume>95</volume>
          /46/EC (
          <article-title>General Data Protection Regulation) (Text with EEA relevance)"</article-title>
          , Op.europa.eu,
          <year>2020</year>
          . [Online]. Available: https://op.europa.eu/en/publicationdetail/-/publication/3e485e15-11bd
          <string-name>
            <surname>-</surname>
          </string-name>
          11e6
          <string-name>
            <surname>-</surname>
          </string-name>
          ba9a
          <article-title>-01aa75ed71a1/language-en.</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          2.
          <string-name>
            <given-names>C.</given-names>
            <surname>Saatci</surname>
          </string-name>
          and
          <string-name>
            <given-names>E.</given-names>
            <surname>Gunal</surname>
          </string-name>
          ,
          <article-title>"</article-title>
          <source>Preserving Privacy in Personal Data Processing"</source>
          ,
          <year>2019</year>
          1st
          <string-name>
            <given-names>International</given-names>
            <surname>Informatics</surname>
          </string-name>
          and Software Engineering Conference (UBMYK),
          <year>2019</year>
          . DOI:
          <volume>10</volume>
          .1109/ubmyk48245.
          <year>2019</year>
          .
          <volume>8965432</volume>
          .
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          3.
          <string-name>
            <given-names>A.</given-names>
            <surname>Pervushin</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            <surname>Ermachkova</surname>
          </string-name>
          and
          <string-name>
            <given-names>A.</given-names>
            <surname>Spivak</surname>
          </string-name>
          ,
          <article-title>"Determination of loss of information during data anonymization procedure,"</article-title>
          <source>2016 IEEE 10th International Conference on Application of Information and Communication Technologies (AICT)</source>
          ,
          <year>Baku</year>
          ,
          <year>2016</year>
          , pp.
          <fpage>1</fpage>
          -
          <lpage>5</lpage>
          , DOI: 10.1109/ICAICT.
          <year>2016</year>
          .
          <volume>7991650</volume>
          .
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          4.
          <string-name>
            <given-names>N.</given-names>
            <surname>Elanshekhar</surname>
          </string-name>
          and
          <string-name>
            <given-names>R.</given-names>
            <surname>Shedge</surname>
          </string-name>
          ,
          <article-title>"An effective anonymization technique of big data using suppression slicing method," 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS)</article-title>
          ,
          <year>Chennai</year>
          ,
          <year>2017</year>
          , pp.
          <fpage>2500</fpage>
          -
          <lpage>2504</lpage>
          , DOI: 10.1109/ICECDS.
          <year>2017</year>
          .
          <volume>8389902</volume>
          .
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          5.
          <string-name>
            <surname>Kyryk</surname>
            <given-names>М.</given-names>
          </string-name>
          , PleskankaN., TymchenkoО.
          <article-title>Methods and models of traffic management in distributed infocommunication systems</article-title>
          . -Lviv: Ukrainian academy of printing,
          <year>2017</year>
          . - 264 p.
          <source>(ISBN 978-966-322-473-2).</source>
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          6.
          <string-name>
            <given-names>V.</given-names>
            <surname>Gadad</surname>
          </string-name>
          and
          <string-name>
            <given-names>C. N.</given-names>
            <surname>Sowmyarani</surname>
          </string-name>
          ,
          <article-title>"A novel utility metric to measure information loss for generalization and suppression techniques in Privacy Preserving Data publishing,"</article-title>
          <source>2019 4th International Conference on Computational Systems and Information Technology for Sustainable Solution (CSITSS)</source>
          , Bengaluru, India,
          <year>2019</year>
          , pp.
          <fpage>1</fpage>
          -
          <lpage>5</lpage>
          , DOI: 10.1109/CSITSS47250.
          <year>2019</year>
          .
          <volume>9031014</volume>
          .
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          7.
          <string-name>
            <given-names>H.</given-names>
            <surname>Garudadri</surname>
          </string-name>
          ,
          <article-title>"Making sense of personal data in clinical settings,"</article-title>
          <source>2014 48th Asilomar Conference on Signals, Systems and Computers</source>
          , Pacific Grove, CA,
          <year>2014</year>
          , pp.
          <fpage>2086</fpage>
          -
          <lpage>2089</lpage>
          , DOI: 10.1109/ACSSC.
          <year>2014</year>
          .
          <volume>7094841</volume>
          .
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          8.
          <string-name>
            <given-names>P. C.</given-names>
            <surname>Kaur</surname>
          </string-name>
          ,
          <string-name>
            <given-names>T.</given-names>
            <surname>Ghorpade</surname>
          </string-name>
          and
          <string-name>
            <given-names>V.</given-names>
            <surname>Mane</surname>
          </string-name>
          ,
          <article-title>"Analysis of data security by using anonymization techniques," 2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)</article-title>
          , Noida,
          <year>2016</year>
          , pp.
          <fpage>287</fpage>
          -
          <lpage>293</lpage>
          , DOI: 10.1109/CONFLUENCE.
          <year>2016</year>
          .
          <volume>7508130</volume>
          .
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          9.
          <string-name>
            <given-names>J.</given-names>
            <surname>Yand</surname>
          </string-name>
          ,
          <string-name>
            <given-names>Z.</given-names>
            <surname>Hu</surname>
          </string-name>
          and
          <string-name>
            <surname>J. Zhang,</surname>
          </string-name>
          <article-title>"Trajectory Privacy Protection Method through Active Points Hiding,"</article-title>
          2018 Eighth International Conference on Instrumentation &amp;
          <article-title>Measurement, Computer, Communication and Control (IMCCC), Harbin</article-title>
          , China,
          <year>2018</year>
          , pp.
          <fpage>1101</fpage>
          -
          <lpage>1106</lpage>
          , DOI: 10.1109/IMCCC.
          <year>2018</year>
          .
          <volume>00229</volume>
          .
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          10.
          <string-name>
            <given-names>S.</given-names>
            <surname>Mahajan</surname>
          </string-name>
          ,
          <string-name>
            <given-names>J.</given-names>
            <surname>Katti</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A.</given-names>
            <surname>Walunj</surname>
          </string-name>
          and
          <string-name>
            <given-names>K.</given-names>
            <surname>Mahalunkar</surname>
          </string-name>
          ,
          <article-title>"Designing a database encryption technique for database security solution with cache,"</article-title>
          <source>2015 IEEE International Advance Computing Conference (IACC)</source>
          ,
          <year>Banglore</year>
          ,
          <year>2015</year>
          , pp.
          <fpage>357</fpage>
          -
          <lpage>360</lpage>
          , DOI: 10.1109/IADCC.
          <year>2015</year>
          .
          <volume>7154730</volume>
          .
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          11.
          <string-name>
            <surname>A. D. Yuniar</surname>
            and
            <given-names>A. S.</given-names>
          </string-name>
          <string-name>
            <surname>Fibrianto</surname>
          </string-name>
          ,
          <article-title>"The Affect of Technical Familiarity and Consumer Protection Behavior in Using E-Commerce as Platform Online Shopping," 2019 International Seminar on Application for Technology of Information and Communication (iSemantic), Semarang</article-title>
          , Indonesia,
          <year>2019</year>
          , pp.
          <fpage>300</fpage>
          -
          <lpage>305</lpage>
          , DOI: 10.1109/ISEMANTIC.
          <year>2019</year>
          .
          <volume>8884265</volume>
          .
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          12.
          <string-name>
            <given-names>P.</given-names>
            <surname>Prabhusundhar</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V. K. N.</given-names>
            <surname>Kumar</surname>
          </string-name>
          and
          <string-name>
            <given-names>B.</given-names>
            <surname>Srinivasan</surname>
          </string-name>
          ,
          <article-title>"Border crossing security and privacy in biometric passport using cryptographic authentication protocol,"</article-title>
          <source>2013 International Conference on Computer Communication and Informatics</source>
          , Coimbatore,
          <year>2013</year>
          , pp.
          <fpage>1</fpage>
          -
          <lpage>7</lpage>
          , DOI: 10.1109/ICCCI.
          <year>2013</year>
          .
          <volume>6466144</volume>
          .
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>