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Towards the Identification of Security Tokens on Ethereum

Towards the Identification of Security Tokens on Ethereum.docx

ABSTRACT

Crypto tokens are digital assets, similar to the coins of a cryptocurrency, except that they do not have their own blockchain or distributed ledger. Rather, they are built on top of an existing one. Areas of application include their use as means of investment, as a local currency in a decentralized application, as well as means for building an ecosystem or a community. Depending on the purpose, it is common to categorize tokens into payment tokens, security tokens and utility tokens. The distinction is of interest since in most jurisdictions, security tokens are more heavily regulated than other tokens. In this paper, we present a heuristic approach towards automatic detection of security tokens from blockchain data. To this end, we first discuss several methods for the (semi-) automatic identification of token contracts. Then we attempt to identify the token type. For our analysis, we examine both the deployed bytecode and the calls to token contracts that we extract from transaction data of the Ethereum main chain up to block 9500000, mined on Feb 17, 2020.

INTRODUCTION

Tokens are seen as the killer application of blockchains and cryptocurrencies. They can act as a medium of exchange similar to a currency. When integrated into a decentralized application, tokens can serve as a local currency. The most outstanding feature is the programmability of tokens – they are managed by small programs that run on a peer-to-peer network with the purpose of automating the exchange of digital assets without the need for an external trusted authority. Such assets may be linked to non-digital objects or values. Crypto tokens have started to change financial processes. Smart contracts facilitate the combination of tokenized assets with coded rules that are automatically enforced. Thereby they cause a shift in trust towards a technology that still has some challenges to solve. Nevertheless, companies already use cryptocurrencies and tokens for funding or enhancing services. Similarly, decentralized finance (DeFi) and FinTech1 are booming. The increasing use of digital assets has alerted governments and stakeholders to seek clarity on regulations, particularly whether assets qualify as securities.A high-level categorization of crypto tokens distinguishes between payment tokens, security tokens, and utility tokens. The distinguishing feature is the investment purpose of security tokens, while utility tokens typically serve the functioning of a product. Payment tokens fulfill a payment role with little or no other function. Classifying a token reliably along these lines can turn into a difficult task, as it may require legal expertise and negotiations with regulatory bodies. We aim at a better understanding of the use and potential of token contracts by analyzing them on a large scale. Due to their number (over 200 000 on Ethereum), classifying them manually on an individual basis is not feasible. An interesting option is to infer their types automatically, at least with some level of confidence. In this paper, we present first steps towards this goal. We focus on Ethereum as the major platform for token contracts, with plenty of data available. Our method analyzes the bytecode of token contracts and extracts characteristic metrics for their interfaces. We hypothesize that these numbers predict to some degree the token type. The qualitative evaluation is based on six token contracts under review by regulatory bodies and nine further contracts from the main chain. Our work contributes to the field of crypto asset analytics by providing a method for their detection and classification.

EXISTING SYSTEM:

The most outstanding feature is the programmability of tokens – they are managed by small programs that run on a peer-to-peer network with the purpose of automating the exchange of digital assets without the need for an external trusted authority. Such assets may be linked to non-digital objects or values. Crypto tokens have started to change financial processes. Smart contracts facilitate the combination of tokenized assets with coded rules that are automatically enforced. Thereby they cause a shift in trust towards a technology that still has some challenges to solve. Nevertheless, companies already use cryptocurrencies and tokens for funding or enhancing services. Similarly, decentralized finance (DeFi) and FinTech1 are booming. The increasing use of digital assets has alerted governments and stakeholders to seek clarity on regulations, particularly whether assets qualify as securities.

DISADVANTAGES:

classifying them manually on an individual basis is not feasible.

PROPOSED SYSTEM:

In this paper, we present first steps towards this goal. We focus on Ethereum as the major platform for token contracts, with plenty of data available. Our method analyzes the bytecode of token contracts and extracts characteristic metrics for their interfaces. We hypothesize that these numbers predict to some degree the token type. The qualitative evaluation is based on six token contracts under review by regulatory bodies and nine further contracts from the main chain. Our work contributes to the field of crypto asset analytics by providing a method for their detection and classification.

ADVANTAGES:

We aim at a better understanding of the use and potential of token contracts by analyzing them on a large scale.

SYSTEM REQUIREMENTSSPECIFICATIONS:

An SRS (software requirements specifications) is a document that describes the nature of an application or a project or software. This report includes the purpose, scope, functional and non- functional requirements of a project. We can also tell this as the description of software system that is to be developed according to a particular model. This is a communication between the clients and software designers/programmers.

The specific  goals are:

 •Facilitating the reviews

 •Information regarding the scope of work

 •Providing a format/structure

•Providing frameworks for primary and secondary testing

 •Platform for on going refinement. The functional requirements are discussed in the below section.

 Software Requirements:

OperatingSystem: Any Windows

IDE: Anaconda

Language: Python 3.7

Hardware Requirements:

• Processor – i3 processor

• RAM – 512 MB(min)

 • Hard Disk – 500 GB

 • Key Board – Standard Keyboard

CONCLUSION

Determining the purpose and the legal status of a token contract in a reliable manner is intrinsically difficult and will remain the realm of experts. Clearly, it is infeasible to classify large quantities of contracts this way. A statistical analysis of all contracts, for gaining e.g. insights into the use of contracts at large, has to rely on other approaches. In this paper, we propose a heuristic method for identifying pure tokens automatically, by checking that their interface offers only token-related and neutral functions. Pure tokens show no sign of a genuine product or service and thus may be security tokens. Of the 188 k contracts on the Ethereum mainchain (as of Feb 2020) that comply with the ERC-20 standard, 77 % are pure tokens. For a qualitative evaluation, we compare the results of our method to the SEC ruling on six tokens. Moreover, we apply our method to nine further tokens after classifying them manually as security or utility token. Our method yields meaningful results that indicate that the prototype, after extending and refining the classification rules for function headers, is suited for a statistical analysis. Even though effective in the case of standardized token contracts, deriving the purpose of a function from its header is a rather crude heuristics. Moreover, it presupposes that the header is actually known. A more general approach requires semantic code analysis to identify behavior typical of certain applications, as well as tools able to perform it automatically on large numbers of contracts.

REFERENCE

[1] Z. Zheng, S. Xie, H.-N. Dai, W. Chen, X. Chen, J. Weng, and M. Imran, “An overview on smart contracts: Challenges, advances and platforms,” Future Generation Computer Systems, vol. 105, pp. 475–491, 2020.

[2] L. Oliveira, L. Zavolokina, I. Bauer, and G. Schwabe, “To token or not to token: Tools for understanding blockchain tokens,” in International Conference on Information Systems (ICIS). AIS eLibrary, 2018.

[3] P. Hacker and C. Thomale, “Crypto-securities regulation: Icos, token sales and cryptocurrencies under eu financial law,” European Company and Financial Law Review, vol. 15, no. 4, pp. 645–696, 2018.

[4] J. Rohr and A. Wright, “Blockchain-Based Token Sales, Initial Coin Offerings, and the Democratization of Public Capital Markets,” Hastings LJ, vol. 70, 2019. [5] M. Mendelson, “From Initial Coin Offerings to Security Tokens: A US Federal Securities Law Analysis,” Stan. Tech. L. Rev., vol. 22, 2019.

 [6] FINMA, accessed 2019-10-12. [Online]. Available: https://www.finma.ch/en/documentation/dossier/dossier-fintech/ entwicklungen-im-bereich-fintech/

[7] SEC, accessed 2020-02-01. [Online]. Available: https://www.sec.gov/ corpfin/framework-investment-contract-analysis-digital-assets

[8] European Parliament and the Council of the European Union, “MIFID II: directive 2014/65/EU,” accessed 2020-01-20. [Online]. Available: https://eur-lex.europa.eu/legal-content/EN/TXT/ PDF/?uri=CELEX:32014L0065&from=EN [9] “Contract ABI Specification,” 2019, accessed 2019-09-09. [Online]. Available: https://solidity.readthedocs.io/en/latest/abi-spec.html

[10] F. Vogelsteller and V. Buterin, “ERC-20 token standard,” 2015, accessed 2019-10-12. [Online]. Available: https://eips.ethereum.org/EIPS/eip-20

March 19, 2022

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