=Paper=
{{Paper
|id=Vol-3077/paper21
|storemode=property
|title=Designing a software for digital forensic investigations of e-petitions voting falsifications
|pdfUrl=https://ceur-ws.org/Vol-3077/paper21.pdf
|volume=Vol-3077
|authors=Ivan I. Kovalenko,Pavlo V. Merzlykin
}}
==Designing a software for digital forensic investigations of e-petitions voting falsifications==
https://ceur-ws.org/Vol-3077/paper21.pdf
Designing a soӀware for digital forensic
investigations of e-petitions voting falsifications
Ivan I. Kovalenko1 , Pavlo V. Merzlykin1
1
Kryvyi Rih State Pedagogical University, 54 Gagarin Ave., Kryvyi Rih, 50086, Ukraine
Abstract
E-petition is a relatively new tool for expressing community demands and inuencing on the legislative
process. An issue of voting falsications detection is rarely considered in e-petition analysis reports.
Within this research, an illegal petition falsication service has been examined and some methods of
voting fabrication detection have been suggested and implemented in mobile app. To illustrate the
discussed techniques, some suspicious activities regarding two popular petitions to the president of
Ukraine were detected.
Keywords
e-petition, falsication, voting, president, Android
1. Introduction
In 2015, the changes to the Law of Ukraine “On Citizens’ Appeals” [1] were introduced, according
to which the Internet-based petitions acquired the legal status as a tool for inuence on the
legislative process. Thus, an e-petition allows, with insignicant limitations, to make an online
appeal to Ukrainian authorities, e.g. president, parliament, local governments etc. It should be
noted that e-petition has no absolute power, it only obliges the authority to examine the issue
and deliver the ocial verdict. Petitions therefore announce the wishes and demands of the
citizens. On the other hand, this relatively new tool may be illegally mishandled in behalf of
inuential individuals or groups.
Since there are no tools for public control of voting process, we are working on creating a
soffiware for detecting possible falsications. In this report we analyze e-petitions to President
of Ukraine, but our approach may be generalized for other e-petition services and even for
social media voting.
2. Overview
First, e-petitions may be abused by corrupted representatives of authorities to force their self-
seeking decisions under the guise of society will. Indeed, they may have access to some personal
CS&SE@SW 2021: 4th Workshop for Young Scientists in Computer Science & Software Engineering, December 18, 2021,
Kryvyi Rih, Ukraine
" ivankovalenko104@gmail.com (I. I. Kovalenko); ipmcourses@gmail.com (P. V. Merzlykin)
~ https://kdpu.edu.ua/personal/pvmerzlykin.html (P. V. Merzlykin)
0000-0002-4017-7172 (P. V. Merzlykin)
© 2022 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073
CEUR Workshop Proceedings (CEUR-WS.org)
97
data of citizens, so it is possible to produce fake votes for protable petitions. The access to
e-petition Internet platform makes it possible to reduce the number of votes if it is benecial to
certain individuals. For example, such activities may have been carried out by related to Kryvyi
Rih city council persons when e-petition service accidentally turned o just before the resonant
petition gained few last votes [2].
There are other issues related to e-petitions cheating. For example, there even exist illegal
services to trade votes for petitions to the President of Ukraine, e.g. [3]. We have contacted
(gure 1) the representatives of the service via chat and they conrmed that it is possible to buy
some voices for a petition to the president of Ukraine. The also assured us that they pay to real
people for signing petitions and it is possible to buy a test package of 50 votes for $25. We have
also found out that their Telegram account is @redzona and the Skype account is god19952.
We have checked the domain and discovered that it belongs to Danesco Trading Limited [4]
which is a registered at Cyprus domain name provider [5]. At the same time, the specied at the
website social network user prole leads to the page of Nikita Kuznetsov [6] who is registered as
a resident of Moscow. This example represents another threat to e-democracy. While corrupted
local authorities technically might be brought to justice, it is not easy to resist external voting
intrusions.
3. The analysis of existing solutions
An example of an organization that analyzes the gain of online petitions votes is the “League
of Interns” NGO [7], which has been examining electronic petitions to the Verkhovna Rada of
Ukraine with the support of the USAID RADA Program [8] carried out by the Eastern Europe
Foundation since March 2017. During this time, e-petitions have monitored and a number
of information and training materials were prepared. For three years in a row, e-petitions
concerning the activities of the Verkhovna Rada of Ukraine, the President of Ukraine, and the
Cabinet of Ministers of Ukraine have been in the lead.
An analysis the “League of Interns” community activities lets us spot a serious approach to
data collection and a signicant amount of data processed. The organization’s task is to analyze
the operation of the mechanism of online voting, its eciency and popularity. They do not
detect possible cheating on the site.
Another statistics on e-petitions that could be found is one provided by the “Communication
for Change” center [9]. This statistics show that Ukrainians are quite active in exercising their
right to inuence the government and consistently submit petitions to address pressing issues
in the country. The statistics covers the hot topics of submitted petitions, the rate of president’s
replies and so on. However, it does not consider any kind of vote gain cheating.
As for foreign e-petition researches, there is an analysis of ve years operation of White
House e-petitions platform, which is called “We the People” [10]. But it generally discusses
the impact and most common subjects of e-petitions. Quite interesting, however, that Russo-
Ukrainian War takes the second place in the top list of foreign policy petitions right affier Middle
East issues.
Another report by Janne Berg [11] addresses the problem of anonymous e-petitions in Finland
and why people decide to conceal their names while signing e-petitions. It mention the fake
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Figure 1: Communication with nakrutka.net sta.
signatures problem, but it is basically out of the research scope.
Taking into account the aforesaid, it could be seen that e-petitions indeed play a signicant
role in public life, but there are no monitoring tools available in Ukraine. The NGOs who
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analyze e-petitions do not even take into account possibilities of falsications. So there is a
need for a tool to detect suspicious activity on particular petitions to attract public attention to
possible falsications.
4. Implementation
We decided to implement our service as a mobile application since it would allow users to
monitor e-petitions they are interested in, and such decentralized approach makes our system
less vulnerable. It is shown on the gure 2. The application consists of active windows and
a service for obtaining up-to-date information about voting on the e-petitions website and
comparing groups of signatories from dierent petitions. For further analysis of the obtained
data, the table with comparison results is also exported. The program has several active windows
(Activities), which may be switched by user.
Figure 2: The e-petition falsification tracking mobile application.
Affier launching the client, one would see a window with a button to manually update the list
of petitions. Main menu is at the top right corner. It includes a button “About the program”,
“Comparison” and buttons to open a list of petitions “Under consideration” or “With answer”.
The rst upgrade process takes about 30 minutes. The service runs in the background, which
does not require to keep the application window open during the entire update time.
Once one have obtained the list of petitions, it is possible to view the voting plot or visit
the petition webpage. The list is arranged according to the number of votes per day. Petitions
with more than 1,000 votes per day are highlighted with red and are at the top of the list. The
petitions, with more than 100 votes a day are also highlighted, but they are not so interesting,
because such vote bursts are common, especially for important petitions. An example is shown
on the gure 3.
Affier clicking the “Plot” button, the user will see the Activity with a chart of daily votes.
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Figure 3: Suspicious petitions highlighting.
“Open page” button leads to the petition webpage. An example is shown on the gure 4.
To compare the signatories of dierent petitions, it is necessary to select the date on the
petition plot from which the signatories will be analyzed. It could be done by clicking on a
specic day of the histogram. The minimum number of petitions to compare is two, but it is
possible to select more.
Affier selecting the days, one need to open the comparison Activity. It could be done by
clicking “Comparison” in the menu. An example of collecting the lists of signatories is shown
on the gure 5.
This activity shows a list of selected petitions, selected dates and number of votes. A long press
on the petition removes it from the list. To start the comparison, one should click “Comparison”
in the menu, then if necessary, it is possible to export the data by clicking the “Export” item in
the menu. An example of the comparison process and its result is shown on the gure 5.
If matches were found, it is be possible to export the table with the list in csv format.
The application is similar to a log in which everyone can view a list of petitions and choose
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Figure 4: Petition chart activity and a petition webpage.
one to view statistics, as well as go to the webpage where it is possible to vote. The data
is updated periodically by timer event, but if one wants to update the list themselves at a
convenient time, there is an update button.
When the application is started, the MainActivity is being created and the AppDatabase
database is being connected. Affierwards, in the basic global class, OnBootReceiver and Alarm-
Reciver broadcast receivers and the intentService service (ForegroundService) are being created.
An adapter PetitionListAdapter for communication with the database is being created to load
data into the PetitionViewModel through the application observer.
The update algorithm looks like this: the parser performs page-by-page analysis of the
petition webpage while there is data. When the information is collected, the analysis of each
petition begins separately and the votes data is obtained.
Affier information accumulation is completed, the data is being written to the database with
page number marks, which is necessary to avoid full webpage parsing next time.
Having data from the petitions, namely the number of votes by date and the list of signatories
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Figure 5: Comparison range selection and comparison results.
who voted for the petition these days, it is possible to compare the lists of people who voted on
specic dates for dierent petitions. If matches were found, the obtained information might
be taken into account. For example it might look suspicious if same persons regularly vote for
dierent petitions within short periods of rapid votes bursts. CompareActivity is responsible
for all this process.
5. An example of use
Although the research is not nished yet, we would be glad to share and discuss our interim
results. The most interesting case is two opposite petitions for and against the resignation of
the president Volodymyr Zelenskyj [12, 13]. Our soffiware helped to detect over 500 persons
who signed both of them during just few days. About half of these matches were detected in
only two most active days of these two petitions (gure 6). Such indicators give reason to think
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about the possible cheating and interference in the voting process. It may be a result of personal
data stealing or votes trading.
Figure 6: A comparison of vote gain dynamics of petitions 53360 and 53988.
6. Conclusion
Since there are no ecient tools for e-petitions cheating revealing, we developed an application
for voting dynamics analysis. We are planning to build a mathematical model to detect suspicious
voting gaining intervals, but due to the lack of completed petitions, we currently use a simplied
model which might be improved in the future. It is possible to extract names of petitioners who
signed petition within time intervals marked as “suspicious” and automatically name-by-name
compare these lists for dierent petitions. The proposed soffiware does not give a nal verdict
but may be used as a tool for detecting evidences of possible falsications.
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