• With unparalleled speed and magnitude, the digital revolution has revolutionized our lives and civilizations and presents enormous potential as well as terrifying challenges. New technologies have the potential to significantly contribute to the achievement of the Sustainable Development Goals, but favourable results cannot be assumed. If we are to fully exploit the social and economic potential of digital technology, while avoiding unpredictable effects, we must urgently strengthen international cooperation. Secretum is a major advance in the decentralization of messaging apps in the sector. Secretum caters to the following client segments: B2B, B2G and C2C:

• What exactly is B2B: A business-to-business transaction occurs when one company does business with another. This usually occurs when a firm sources resources for its output production process, i.e. it gives raw materials to another company that will produce the outputs.

• What exactly is B2G: Business between the private sector as a supplier and a government entity as a client is referred to as business-to-government or business-to-administration.

• What exactly is C2C: Customer to customer (C2C) is a business concept in which customers do business with each other, usually over the Internet.

• B2B and B2G markets

Users from business and government

Cyber and industrial espionage represent a rising danger and economic harm to corporations throughout the globe. IP theft, NFT, and trade secret theft are projected to cost the world economy $445 billion each year, with estimates ranging from $600 billion to $1 trillion. Governments and state actors are likewise aware of the threats presented by hacks that result in the release of diplomatic papers, embarrassing information about politicians, public service interruptions, or the revelation of sensitive defines-related data.

Furthermore, NFT has modest implementation costs while paying out large sums of money: According to Deloitte, a cyber assault costing as little as $34 per month might yield up to $25,000 in damages. In 2020, the average cost of a data breach to a firm was $3.86 million globally, and $8.64 million in the United States.

NFT revenues outnumber worldwide cybersecurity expenditure by a factor of ten. Governments and multinational corporations are actively pursuing all-encompassing communications solutions to prevent the financial, operational, and reputational risks that data breaches and NFT pose.(Worldwide market size: 300-500 million people)Owners of Small and Medium-Sized Businesses Due to their weak cybersecurity measures, limited funds to adopt any, and limited desire to encrypt database and communications data, SMEs are the most susceptible to cyber assaults.75 percent of all SMEs are expected to lack a cybersecurity strategy or funding to secure their operating systems, private conversations, or sensitive data. The facts, on the other hand, indicate a genuine and present risk, with: Small enterprises are the target of 43% of cyber assaults. Sixty percent of small firms that are the victims of a cyber assault fail within six months.

A data breach may cost a small organisation over $25,000 on average. The Covid-19 epidemic has accelerated the growth of smart working and remote working, making SMEs increasingly more dependent on instant messaging between workers and management. Furthermore, with over 90% of small companies employing cloud-based storage solutions, data security threats remain high. To safeguard their databases and internal messages, this sector seeks an easy-to-use, cost-effective, adaptable, and encrypted solution.(Worldwide market size: 130-150 million people) Advantages Easy Communication on the Move: Government officials are regularly traveling and out of the office. Zangi provides fast messaging and easy exchange whenever and wherever required. Call from abroad and still be directly connected to your communication system, while avoiding roaming charges.

• The B2C Market

This is the typical person who is aware of the hazards associated with present messaging applications, social media, and mobile communications. A person who cherishes the privacy of their private communications, data, and images, and wishes to keep them secure from hackers and the authorities.(Global population: 600-700 million people)

• Celebrities and High-Net-Worth Individuals

These are people who have a great interest in protecting their movements, assets, and personal data against cyber attacks because of their enormous fortune, public visibility, and personal power. They also wish to prevent real-life hazards (such as kidnappings or assaults) that might arise from their personal conversations or data not being protected.(Worldwide market size: 20-50 million people)

• Cryptocurrency Users

These are those who wish to keep their crypto safe while communicating with other crypto users and trading crypto assets safely. In less than six months, the worldwide number of crypto users quadrupled from 106 million in January 2021 to 221 million in June 2021, making this the fastest-growing user demographic targeted by Secretum.(Worldwide market size: 250 million people)

Data and Methodology

Our data set includes 1231 daily observations from 1 January 2018 to 16 May 2021 on the amount of NFT sales in USD, the number of blockchain wallets storing or using NFTs, and the price of ETH and BTC in USD. The first two measurements are taken from NonFungible Corporation (nonfungible.com) and solely include information on the Ethereum blockchain, which historically has accounted for the majority of the NFT industry. The source of price data (daily close) is the cryptocurrency exchange Bitfinex (bitfinex.com); for daily data, this source is less vulnerable to big cryptocurrency exchanges or data aggregators. According to Dowling (2021a), we utilise ETH, the most relevant currency for issuing and trading, as our reference market for cryptocurrencies.

Since early 2021, the trading volume of NFTs has increased dramatically, as seen in Figure 1. For instance, on the single day of May 3, 2021, nearly $100 million worth of NFTs were exchanged, while the year's average daily trading volume ($6.13 million, compared to $0.18 million in 2020, $0.07 million in 2019, and $0.10 million in 2018) has been significantly greater than in prior years.

Figure 5: NFT and cryptocurrency market data

Figure 5:(a) ETH price in USD between January 2018 and May 2021; (b) the number of active NFT wallets on the Ethereum blockchain between January 2018 and May 2021; (c) BTC price in USD between January 2018 and May 2021. (a) Sales of NFT in USD million. (b) The quantity of open NFT wallets. (c) the USD price of ETH. (d) The cost of bitcoin in US dollars. The graph demonstrates that there are now many more wallets on the Ethereum blockchain that are holding NFTs. For instance, more than 5700 distinct wallets held NFTs in March 2021. The two measures amply demonstrate how NFTs are becoming more and more relevant in terms of market volume and user count, as measured by the number of blockchain wallets. The two cryptocurrencies also reached their all-time highs in 2021, at $63,537 (BTC) and $4172 (ETH), respectively, after trading at much lower prices earlier. Table A1 provides descriptive statistics on the raw series, log series, and log differences.

We provide a VAR framework that can be used to systematically evaluate the connections between various variables in order to study the link between the NFT market and cryptocurrencies. Here, we represent vectors of variables as being dependent on both their own and other variables' lags.With our four variables, the VAR model takes the following form:

(1)

where A1 to A4 are the coefficients of a 4 by 4 matrix and a0 is a vector of intercept terms. The Akaike information criterion identifies 4 as the ideal number of delays in our instance (AIC). VAR is an appropriate approach since all four time series are non-stationary in their logarithmic forms and all log differences are stationary (see Table A2). The VECM—the cointegrated VAR—is our model of choice since the Johansen test of cointegration [20] only finds one cointegrating link (cf. Table A3).

Results

To explain the cointegrated VAR's results, we give two postestimation statistics in the sections that follow. Short-run Granger causality test data are shown in Table 1 and show whether a change in one variable occurs before a change in another. For each combination of our dependent and independent variables, the statistics are computed. For instance, the test to determine whether all coefficients on four lags of NFT wallets, which may serve as a possible predictor of NFT sales, are zero is indicated in the first line of results. We cannot affirm that Granger-caused NFT wallet sales are a result of NFT sales since the p-value is greater than the significance cutoff of 10%. However, Granger-caused NFT sales are brought on by the BTC price.

Figure 6: The table shows short-run Granger causality test statistics for the VECM model.

Additionally, the price of ETH is a Granger-caused factor for NFT wallets. While ETH is Granger-caused by the other variables, BTC is Granger-caused by the price of BTC. As a result, we discover that bitcoin pricing has an impact on NFT markets, even if Granger causality does not provide any information regarding the direction of these affects. Figure 2's depiction of impulse response functions enables us to comprehend that direction of effect. They show the effects of a standard deviation shock to one variable on another over the course of 30 days. One answer is put in each column and one impulse is put in the reach row.

Figure 7: Impulse response functions. Impulse response functions based on the VECM with four lags are shown for a time horizon of 30 days.

Since series are counteracted over the long run, unlike the VAR, VECM impulse response functions do not necessarily need to revert to their mean value. We discover that price hikes in BTC and ETH caused by a single standard deviation shock have a favourable impact on NFT sales. For BTC and ETH, the impacts plateau at about 0.03% and 0.015%, respectively. The number of active NFT wallets is clearly positively impacted by bitcoin price shocks. Surprisingly, the price of ETH has the opposite effect. NFT sales and the quantity of NFT wallets are as anticipated.

Positive connections the short-term price of ETH is negatively impacted by a 1% price shock in BTC. The trend changes direction after approximately 5 days and settles at a permanent impact of roughly 0.001%. BTC's price responds favourably (by 0.032%) to an ETH price shock. Impulse response functions must be read carefully for VECM models due to the long-term equilibrium relationship between the series. They support the findings of the short-run Granger causalities discussed above and aid in understanding the fundamental links between the variables, mapping short-run effects, and interpretation.