Accounting in the fourth industrial revolution: Exploration of digital currency exchanges using AHP method

Purpose: The present study aimed to analyze and select the best exchange in the field of digital currencies with a futuristic perspective. Research methodology: The research method in this article is to use Analytic Hierarchy Process (AHP) to identify the strengths and weaknesses of each of these exchanges and analyze their coefficients according to the criteria of security, support, commission, number of currency codes, authentication, and trading volume. Results: The most important criteria in choosing the best digital currency exchange are: security, support, commission, number of currency codes, authentication and trading volume. Limitations: The limitations of this research can be the characteristics of digital exchanges in the field of providing digital currency cryptographic services in accordance with the framework of the Fourth Industrial Revolution. Contribution: According to the weight of the obtained criteria will be prioritized, which from the results and analysis obtained in this research can be used to invest in the field of currency cryptography and select the top exchange

Hidden in Plain Sight: Exploring Encrypted Channels in Android apps

As privacy features in Android operating system improve, privacy-invasive apps may gradually shift their focus to non-standard and covert channels for leaking private user/device information. Such leaks also remain largely undetected by state-of-the-art privacy analysis tools, which are very effective in uncovering privacy exposures via regular HTTP and HTTPS channels. In this study, we design and implement, ThirdEye, to significantly extend the visibility of current privacy analysis tools, in terms of the exposures that happen across various non-standard and covert channels, i.e., via any protocol over TCP/UDP (beyond HTTP/S), and using multi-layer custom encryption over HTTP/S and non-HTTP protocols. Besides network exposures, we also consider covert channels via storage media that also leverage custom encryption layers. Using ThirdEye, we analyzed 12,598 top-apps in various categories from Androidrank, and found that 2887/12,598 (22.92%) apps used custom encryption/decryption for network transmission and storing content in shared device storage, and 2465/2887 (85.38%) of those apps sent device information (e.g., advertising ID, list of installed apps) over the network that can fingerprint users. Besides, 299 apps transmitted insecure encrypted content over HTTP/non-HTTP protocols; 22 apps that used authentication tokens over HTTPS, happen to expose them over insecure (albeit custom encrypted) HTTP/non-HTTP channels. We found non-standard and covert channels with multiple levels of obfuscation (e.g., encrypted data over HTTPS, encryption at nested levels), and the use of vulnerable keys and cryptographic algorithms. Our findings can provide valuable insights into the evolving field of non-standard and covert channels, and help spur new countermeasures against such privacy leakage and security issues.Comment: Extended version of an ACM CCS 2022 pape

Predicting Bitcoin Returns Using Artificial Neural Networks - An Application of Large Datasets to Convolutional Neural Networks and Long Short-Term Memory Based Artificial Neural Networks in Finance.

Time series forecasting is one of the foremost challenges studied in finance. In this thesis various Convolutional Neural Network and Long Short Term Memory Artificial Neural Network models are used to predict Bitcoin returns. Previous literature has explored using data from Sentiment analysis of Social Media, and Blockchain information in isolation. This thesis seeks to combine the predictive power of earlier smaller models into a larger model that better utilizes a broader category of features in time series prediction. The resulting models are able to predict Bitcoin returns well, beating out simpler methods that do not utilize Artificial Neural Networks

Hybrid genetic algorithms in agent-based artificial market model for simulating fan tokens trading

In recent years cryptographic tokens have gained popularity as they can be used as a form of emerging alter- native financing and as a means of building platforms. The token markets innovate quickly through technology and decentralization, and they are constantly changing, and they have a high risk. Negotiation strategies must therefore be suited to these new circumstances. The genetic algorithm offers a very appropriate approach to resolving these complex issues. However, very little is known about genetic algorithm methods in cryptographic tokens. Accordingly, this paper presents a case study of the simulation of Fan Tokens trading by implementing selected best trading rule sets by a genetic algorithm that simulates a negotiation system through the Monte Carlo method. We have applied Adaptive Boosting and Genetic Algorithms, Deep Learning Neural Network-Genetic Algorithms, Adaptive Genetic Algorithms with Fuzzy Logic, and Quantum Genetic Algorithm techniques. The period selected is from December 1, 2021 to August 25, 2022, and we have used data from the Fan Tokens of Paris Saint-Germain, Manchester City, and Barcelona, leaders in the market. Our results conclude that the Hybrid and Quantum Genetic algorithm display a good execution during the training and testing period. Our study has a major impact on the current decentralized markets and future business opportunitiesThis research was funded by the Universitat de Barcelona, under the grant UB-AE-AS017634

Blockchain Value Creation Logics and Financial Returns

With its complexities and portfolio-nature, the advent of blockchain technology presents several use cases to stakeholders for business value appropriation and financial gains. This 3-essay dissertation focuses on three exemplars and research approaches to understanding the value creation logics of blockchain technology for financial gains. The first essay is a conceptual piece that explores five main affordances of blockchain technology and how these can be actualized and assimilated for business value. Based on the analysis of literature findings, an Affordance-Experimentation-Actualization-Assimilation (AEAA) model is proposed. The model suggests five affordance-to-assimilation value chains and eight value interdependencies that firms can leverage to optimize their value creation and capture during blockchain technology implementation. The second essay empirically examines the financial returns of public firms\u27 blockchain adoption investments at the level of the three main blockchain archetypes (private-permissioned, public-permissioned and permissionless. Drawing upon Fichman\u27s model of the option value of innovative IT platform investments, the study examines business value creation through firm blockchain strategy (i.e., archetype instances, decentralization, and complementarity), learning (i.e., blockchain patents and event participation), and bandwagon effects using quarterly data of firm archetype investments from 2015 to 2020. The study\u27s propensity score matching utilization and fixed-effects modeling provide objective quantification of how blockchain adoption leads to increases in firm value (performance measured by Tobin\u27s q) at the archetype level (permissionless, public permissioned, and private permissioned). Surprisingly, a more decentralized archetype and a second different archetype implementation are associated with a lower Tobin\u27s q. In addition, IT-option proxy parameters such as blockchain patent originality, participation in blockchain events, and network externality positively impact firm performance, whereas the effect of blockchain patents is negative. As the foremost and more established use case of blockchain technology whose business value is accessed in either of the five affordances and exemplifies a permissionless archetype for financial gains, bitcoin cryptocurrency behavior is studied through the lens of opinion leaders on Twitter. The third essay this relationship understands the hourly price returns and volatility shocks that sentiments from opinion leaders generate and vice-versa. With a dynamic opinion leader identification strategy, lexicon and rule-based sentiment analytics, I extract sentiments of the top ten per cent bitcoin opinion leaders\u27 tweets. Controlling for various economic indices and contextual factors, the study estimates a vector autoregression model (VAR) and finds that finds that Bitcoin return granger cause Polarity but the influence of sentiment subjectivity is marginal and only stronger on bitcoin price volatility. Several key implications for blockchain practitioners and financial stakeholders and suggestions for future research are discussed

RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization

EDI control : management and audit issues

https://egrove.olemiss.edu/aicpa_guides/1419/thumbnail.jp