=Paper=
{{Paper
|id=Vol-3187/short8
|storemode=property
|title=Ensuring Data Security in the Peer-to-Peer Economic System of the DAO (short paper)
|pdfUrl=https://ceur-ws.org/Vol-3187/short8.pdf
|volume=Vol-3187
|authors=Sergiy Obushnyi,Denis Virovets,Hennadii Hulak,Artem Platonenko,Roman Kyrychok
|dblpUrl=https://dblp.org/rec/conf/cpits/ObushnyiVHPK21
}}
==Ensuring Data Security in the Peer-to-Peer Economic System of the DAO (short paper)==
https://ceur-ws.org/Vol-3187/short8.pdf
Ensuring Data Security in the Peer-to-Peer Economic System
of the DAO
Sergiy Obushnyi1, Denis Virovets1, Hennadii Hulak1, Artem Platonenko1,
and Roman Kyrychok1
1
Borys Grinchenko Kyiv University, 18/2 Bulvarno-Kudriavska str., Kyiv, 04053, Ukraine
Abstract
The article raises the problem of using in DAO, has a high level of interaction with
participants and participants, makes decisions, including using it with the help of autonomous
economic agents. The article also provides a general description of the risks and issues that
need to be addressed for the trusted use of peer-to-peer data in a DAO. In addition to this
presented DAO decision making model, which can be used for investment, commercial and
administrative models for DAOs.
Keywords1
P2P economy, cryptoeconomics, decentralized autonomous organization, DAO, blockchain,
Big Data, data management, autonomous agents.
1. Introduction
Modern digital innovation technologies, such as P2P networks, blockchain, artificial intelligence
and social networks, combined with methods of data collection and processing, being partly or
completely decentralized, represent new opportunities at several levels of economic relations. In the
context of digitalization of the economy, new forms of cooperation as Decentralized autonomous
organizations (hereinafter - DAO) are becoming relevant with a simultaneous reduction of the role of
intermediaries. Increasing the number of electronic communication devices and sensors actually lead
to the creation of new forms of cooperation, where borders and distances will not be an obstacle to
combine human efforts and resources, with increasing information exchange and strengthening data
quality requirements. Decentralized autonomous organizations as effective substitute for the
institution of economic mediation and traditional forms of commercial cooperation, represent a new
form of data collection and management mechanism with the purpose to organize human and digital
resources for digital or real product production.
Despite the wide coverage of the possibilities of working with DAO, the issue of building
decision-making models in DAO has been little studied. Similar to the strategic and tactical
challenges faced by traditional corporations, the digital nature of data makes it imperative to take data
security into account when making decisions. At the same time, given the adaptability of the data,
today there are practically no peer-to-peer databases available for free and safe use in DAOs. Recent
developments in the field of blockchain have shown the possibility of using such databases from
different peer-to-peer systems, subject to certain conditions for data adaptation. In addition, to date,
systems for safe and relatively inexpensive data storage and transmission have been tested, which
opens up new opportunities for using data in DAO.
In this article, we describe the potential for effective big data analytics through enhanced security
and privacy, as well as an effective management system of DAO, fully protected by blockchain, and
joint investment and control of digital assets through a DAO as a new form of cooperation.
CPITS-II-2021: Cybersecurity Providing in Information and Telecommunication Systems, October 26, 2021, Kyiv, Ukraine
EMAIL: s.obushnyi@kubg.edu.ua (S. Obushnyi); seito@ukr.net (D. Virovets); h.hulak@kubg.edu.ua (H. Hulak);
a.platonenko@kubg.edu.ua (A. Platonenko); r.kyrychok@kubg.edu.ua (R. Kyrychok)
ORCID: 0000-0001-6936-955X (S. Obushnyi); 0000-0003-4934-8377 (D. Virovets); 0000-0001-9131-9233 (H. Hulak); 0000-0002-2962-
5667 (A. Platonenko); 0000-0002-9919-9691 (R. Kyrychok)
Β©οΈ 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 (CEUR-WS.org)
284
We believe that competent structuring of the process of managing and storing data will create new
forms of digital cooperation models for the redistribution of digital assets and creation of products.
2. Actuality of the Problem
The problem of using data in peer-to-peer systems and its application with decision making
models began to be investigated from the moment of the active development of cryptocurrencies and
the distribution of digital products on the blockchain, and has been presented in many articles since
2013. In the context of decentralized cooperation, where it is permissible to use data in different DAO
nodes, it is necessary to take into account the structure and type of data, the conditions of their
existence and characteristics in order to effectively use them.
Both current and new projects in the digital economy, based on real or digital business, in their
development, will be characterized by application of certain financial or technical information. The
incoming data in real time will characterize the state of the blocks at a certain point, as well as the
disclosure project development characteristics. Investors will be able to timely receive information via
digital communication channels without fear of risks of privacy, integrity and authenticity of project
data. Such characteristics are achieved by ensuring the security of data at the stage of their collection,
transmission, storage, processing and receipt through the use of modern encryption technologies.
We consider DAO as a self-organizing dynamic information system, the goal of which is self-
development in a digital world with a high level of risks and opportunities. It is expected that a
significant number of decisions in digital markets will be made using big data and decentralized tools
for their analysis, and the consumers of the information obtained in this way will be autonomous
agents and decentralized autonomous organizations in P2P systems.
Despite the study of the meaning of data in peer-to-peer systems, the issue of using data in smart
contracts and DAOs remains rather unexplored. However, it is worth paying attention to some works
where the authors come close to studying data in the blockchain and the importance of their security.
Thus, in the description of the Libonomy project, the idea of implementing a project using peer-to-
peer data was presented [1], and the issue of the integrity of the data used was also raised in a number
of articles on robonomics [2]. Within the framework of domestic science, the issue of using data using
blockchain was discussed within the framework of studying the use of blockchain tools within
economic systems. In addition, a number of papers describe advanced modern mechanisms for
reducing time and costs when using data in peer-to-peer projects, while ensuring their security [4] [5]
[6].
3. Nature and Role of Data in DAO
In the real world, information content increases logarithmically, not linearly. It is believed that in
the modern world the period for doubling information is 18 months [19]. In information theory, this
looks like a significant increase in the amount of information, including information processed per
unit of time. In the biological world, the newer circuits are formed in the human brain, the more
information a person is able to grasp in the simplest and most ordinary objects and events. In analogy
with this, the same information networks can be created in DAO systems. However, raw information
alone does not provide much value. Information becomes valuable after its interpretation and
processing for the purpose of its further effective use. In peer-to-peer systems, this work is called
peer-to-peer management. The flow of information, organized into qualitative structures, resembles
neural connections in the human brain in its constantly renewing dynamic environment. At the same
time, professionally structured connections have an advantage over human perception, since such
connections cannot be resisted by inconvenient information. The difference in the characteristics of
the data of a conventional digital system from P2P data indicates the impossibility of using their
traditional classification, processing and analysis methods [20].
Conventionally, information and data that are valuable in the DAO environment, including those
that are significant for making investment decisions, can be divided into the following categories:
personal information (data on DAO leaders, their qualifications and experience); technical
information (technical data of the project, results of preliminary studies, created samples, expert
285
opinions, technical data sheet, technical forecasts, sensor data); financial information. At the same
time, in the DAO system, it is possible to build analytical nodes capable of providing, in the required
form, key information that potential investors would like to have before making any investment
decisions in relation to the DAO or decisions in its system. Any financial information, including about
income and expenses, the volume of services sold, information about assets can dynamically come to
investors who have appropriate access to it. This information can be supplemented by real-time sensor
data. Access to data can be provided through smart contracts tied to project tokens, confirming
ownership of a stake in the project. Also, through other peer-to-peer tools. This raises the need for
data management, as well as ensuring their security during their transfer and storage.
The role of information in the work of the DAO is obvious. Participants are interested in receiving
key information for making any investment decision. Financial information also helps to identify
trends in business development in its development to understand development trends and future
results [13]. The so-called informational neural connections in the DAO make it possible to build a
high-quality internal search by functions, users and semantic connections. Thus, each DAO can have
its own search engine tailored to the needs of the participants and the goals of the DAO.
Since the launch of the Bitcoin system, projects have been developing related to the exchange of
data in decentralized independent systems. The high cost and low bandwidth of p2p networks
hindered the development of projects allowing to process and store large amounts of data. With a
decrease in the cost of transactions on the network and an increase in speed, projects have become
possible with the creation of a DAO, where the bulk of the work is concentrated on data management,
while ensuring data security and eliminating vulnerabilities in smart contracts and protocols remain
one of the urgent problems of DAO architects.
Table 1
Modern P2P Platforms and Their Features
Operator Lunching Operations per second Transaction fees,
USD $
Bitcoin 2009 7 23
Ethereum 2015 100 000 5
Polkadot 2020 1 000 0.5
Solana 2020 65 000 0.00025
Bitcoin Lightning 2021 1 000 000 0.00055
Network
Modern systems promise to provide flexible data integration and exchange with low installation
and maintenance costs. However, the creation of such systems raises many problems. In addition to
the obvious scalability issue, the selection of appropriate semantics that can deal with arbitrary, even
circular topologies, data inconsistencies or updates, and at the same time allow flexible reasoning, has
been an area of active research [18]. An overview of data management in P2P systems focuses on the
use of indexes, clustering, replication and query processing in such systems [18].
A decentralized environment is attractive for economic development, primarily the ability to
quickly exchange information, while maintaining its integrity and autonomy. Data security is ensured
by the digital peer-to-peer environment, which provides the ability for any kind of encryption and
cryptography. The modern level of technology makes it possible to exchange information safely and
cheaply, which should positively affect the development of the peer-to-peer economy.
In the modern world for companies of all spheres and types have an important role. Companies are
struggling to respond to emerging threats and security challenges of big data in the traditional sense
[36], including the need to study and understand the main risks. Fake Data Generation Employee
Negligence Employee Theft Lack of Security Audits Lack of Security Spending Data Cleansing
Problems Data masking are fairly well-researched risks for working with traditional data [18] [17]. By
understanding the most serious threats, stakeholders can develop more effective mitigation and
response measures. The same approach is observed in the study of the risks associated with the use of
data in a peer-to-peer environment in order to use it for DAO purposes.
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P2P systems do not require centralized management and are not developed under the control of a
central authority. Each peer provides a piece of common information available from a distributed
environment and acts as a client and a server on the system. The result is a completely decentralized
architecture that is flexible and capable of handling dynamic changes in the system to which peers can
join or exit at runtime [9]. Tools for ensuring data integrity and adaptability of topologies in P2P
systems and application integration are described in [31]
4. Data Sources for DAOs and their Security
Blockchain technology is the main tool for securing P2P data today. As a fundamental technology
for the creation and operation of cryptocurrencies, blockchain is a tool that allows you to securely
conduct online transactions using smart contracts, implement transactions, store and process data, and
much more. In blockchain technology, each P2P network node has its own real-time database, which
constantly updates the data and takes a snapshot of the state of the data at the current time. Each of the
nodes in the network offers its own block in the chain. Other nodes on the network check the block,
receive it after checking, and write the block to the chain. Thus, it is believed that it is impossible to
hack the network, since it is stored on several nodes in the network. Thus, the security of operations in
blockchain networks is ensured by the following factors: decentralization of the system; reliability of
encryption algorithms; control and verification system of blocks.
Scope refers to a wide range of data from multiple sources; Diversity refers to different types of
data collected, for example, video, audio, images and text, from various sources such as sensors,
social media, smartphones, others; Speed refers to the speed at which data is collected and processed.
Big data research focuses on methods, technologies, systems, practices, methodologies and
applications that transform big data into useful, relevant and timely information, helping an enterprise
to better understand its business and market conditions and make appropriate decisions [26].
The availability of big data from a variety of sources, with different data formats and sizes, can
provide a more complete picture of the borrower. P2P lending platforms use a wide range of data to
assess credit risk, while traditional banks may not have the technical capacity or analytical skills to
leverage these new forms of data. Moving beyond traditional simplified credit risk indicators such as
applicant assets, existing liabilities and FICO scores, P2P lending platforms analyze more dynamic
data points from public websites, agencies, and public records [26].
5. Decision Making Model in DAO
The digital nature of the blockchain and its capabilities allow the use of any programmable
approaches, including the use of autonomous economic agents, machine learning blocks, decision-
making systems, automatic data retrieval, etc. Such tools can independently, or using other tools,
conduct a search data, process them and independently make decisions.
As an example, below is one of the decision-making models for DAO, based on the management
of data. The choice of the most optimal (digital) solution from offered decisions (by participants,
managers, specialists, etc.), that should be solved automatically (or by way of comparison) is carried
out by comparing the possible benefits, each of which is calculated using the following formula:
π·π = β π¦ β |β π₯| β |π| β |π| β |π|, (1)
where,
y - discounted future benefits with a positive result, taking into account the probabilities.
x - discounted losses that can occur in case of a negative result, taking into account the
probabilities.
a - offered solutions cost, taking into account the probability of failure.
b β additional expectations from a positive result
c - discounted indirect costs associated with the decision.
287
Benefits and losses, as well as the cost of a solution, can be expressed both in direct price,
expressed in electronic digital units, and in the cost of resources. In turn, each of the parameters can
be calculated as follows:
π¦π π¦π (2)
π¦ = β( π‘π
)+( ) β π,
(1 + π
) (1 + π
)π‘π
π₯π π₯π (3)
π₯ = β( π‘
)+( ) β (1 β π),
(1 + π
) (1 + π
)π‘
ππ β πππ (4)
π = β( ),
(1 + π
)πππ
ππ (5)
π = β( ) + ππ β (1 + π
)ππΉπ ,
(1 + π
)ππΉπ
π = β(ππ β (1 + π
)πππ ), (6)
where,
R - discount rate (rate proposed by validing of the principal cryptomoney (cryptoassets))
P - probability of a positive result when implementing a specific decision
t - time required to implement the solution
TP - time point for payment (resource costs)
WP - weights of resource payment values
TF - time of payment of direct costs for the solution
TV - the time of payment for the payment of indirect costs for the implementation of the solution
The results of applying this model using these hypothetical solutions after implementing the model
in the Matlab environment are as follows:
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Figure 1: Decisions indifference planes
The plotted graph characterizes the planes of decisions indifference, where possible benefits are
equal to losses. In this case, the points characterize each of the solutions in their weight of benefits
(above the plane) and losses (below the plane).
A number of parameters, such as discount rate, timing of events, possible decision costs and
probabilities, can be calculated in the DAO, either through the involvement of experts or independent
agents, or through automatic database searches.
6. Data Problems for DAO
A decentralized environment also saves personal risks, including those associated with a lack of
user experience. For example, an inexperienced user might enter a wrong address and the money will
be transferred to a completely different person or company. In this case, no return is possible [16].
However, it seems possible to develop and implement algorithms in DAO to control and reduce risks,
including personal risks.
It is believed that a fundamental problem in most P2P systems is data placement and retrieval [37].
Due to its characteristic of decentralization, blockchain has properties of protection against
unauthorized access, non-forgery, privacy protection and automatic execution of smart contracts, due
to which blockchain technology has a wide range of application scenarios, including use for storing
data and recording transactions. The process of verifying, accounting, storing, maintaining and
transmitting data in the blockchain is based on the structure of a distributed system, and not on a
centralized mechanism for building trust relationships between nodes. The underlying blockchain data
layer is supported by techniques such as hashing, asymmetric encryption, Merkle tree and timestamps
[14].
The blockchain-based p2p data storage scheme has a significant improvement in system
performance compared to conventional cloud storage schemes [14]. Previous old blockchain systems
289
based on proof-of-work methods are characterized by slow data processing and high cost of
operations. This problem can be solved using a tool such as creating a Lightning network. Such a
network basically consists of two contracts: the sequence expiration revocable contract (RSMC) and
the hash time fixed contract (HTLC). Decentralized data storage based on blockchain is provided by
cryptographic methods, including tools such as the Lightning Network technology and remote data
integrity confirmation technology [24].
Expiration of the sequence can solve the problem of fast two-way transmission between the two
sides of the channel. The hash time blocking contract solves the problem of transmission between
nodes. These two types of trading portfolios form a lightning fast web. The payment method in this
system is basically a one-way payment between two users, so the system basically uses a revocable
contract with an expiration date to implement unlimited fast offline transfer between two users. The
load of data and the amount of data entering the network can be determined by the tools for
characterizing the network behavior of P2P traffic. For example, a developed measurement method,
the Content Transfer Index (CTI), distinguishes between two classes of P2P traffic behavior:
download and signaling traffic profile. If the download traffic is based on the analysis of the content
transfer, the second is mainly related to the presence of an overlay network and possibly a search
service. A way to separate download traffic from signaling traffic is to implement a protocol analyzer
[12].
Data management issues in DAOs that need to be addressed when dealing with the scale and
instability of such systems include:
ο· Location of data: peers must be able to refer to and find data stored in other peers
ο· Query handling: Upon request, the system must be able to discover peers that provide the
appropriate data and execute the request efficiently.
ο· Data Integration: When data sources shared in the system follow different schemas or views,
peers should still be able to access that data, ideally using the data view used to model their data.
ο· Data consistency: If data is replicated or cached in the system, maintaining consistency
between these duplicates is a key issue [21].
However, despite their advantages, P2P systems offer limited data privacy guarantees. They can be
viewed as hostile because data, which may be confidential or confidential, could be available to
everyone (potentially untrustworthy partners) and used for everything (for example, for marketing,
profiling, fraud, or for actions contrary to the preferences or ethics of the owner). Several P2P systems
offer privacy mechanisms such as OceanStore, Past, and Freenet. However, these solutions are not
enough [22].
Ensuring anonymity in the system is required at the following levels: personal data and access to
data and the system, personal priorities and hobbies, data from social networks and the Internet
environment [27]. An overview of current solutions for maintaining data privacy in P2P systems and a
complete solution based on HDB (Hippocrates Database) is being developed in more detail [22].
Authorization and privacy management is ensured by controlling the availability of data at the peers.
In general, each peer in the system can independently authorize access to its data in response to
guarantees of confidentiality or confidentiality of the data. Thus, each participant can independently
determine the data privacy policy [20].
As example new blockchain storage "Mystiko", built on the basis of Apache Cassandra distributed
database, offers a solution for storing big data. Mystiko supports high transaction throughput, high
scalability, high availability, and full text search functionality. Mystiko provides big data with
security, structure and meaning, and simplifies further big data analytics [23].
It is impossible to guarantee the absolute security of peer-to-peer data for, just as it is impossible to
do this with respect to any other processes and technologies. Participants of the DAO, given the
architecture of the organization, ways to reduce risks by encouraging and encouraging careful
handling of data and carefully analyze the possible presence of fraud [16]. A digital outsourced
security system is also possible if appropriate solutions are provided for by the DAO protocols.
Data management in distributed systems can be provided by distributed database systems that
allow users to transparently access and update multiple databases on the network using a high-level
query language [11]. The most popular in the market are two types of databases, such as relational
(SQL) or non-relational (NoSQL). However, due to the peculiarities of the blockchain for DAO
290
purposes, it is necessary to adapt systems to the structure of the databases, due to problems with
scalability, low transaction speed, and many others. We cannot completely replace traditional
database architectures, so it is obvious to combine blockchain functions with existing databases [10].
Distributed database systems (DDBS) are used when data is fragmented and administration is
concentrated on a single node. Solutions built on the basis of DDBS can solve the problem of
managing several dozen databases [29]. The practical use of such databases with the help of artificial
neural networks is described in the project for assessing the rating of tourist profiles [32].
In addition, the dynamic nature of the system can impose certain restrictions on the consistency
and availability of data: if the rate at which data changes in the system is high, then the overhead of
maintaining globally accessible indexes may become unacceptable as the number of peers in the
system grows [37].
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