Background: Within the emerging field of cryptocurrencies, the sub-sector DeFi (decentralized finance) has experienced explosive growth over the last year, and its importance for crypto as a whole has grown with it. The currencies have developed from simple peer-to-peer transactions to complex applications such as lending and exchanges. Several studies have researched determinants of cryptocurrency prices, and a few have focused on metrics central to DeFi, such as total value locked (TVL). However, academia has aimed sparse attention to the relationships between these metrics, which this article seeks to amend.  Aim: The purpose of this essay is to research the relationship between total value locked (TVL) in DeFi, the prices of native tokens on related platforms, and the price of ether, which is the dominant currency across DeFi.  Methodology: This study is deductive and quantitative and categorized as a causal-comparative thesis. The purpose of causal-comparative research is to find relationships between variables, independent and dependent, over a certain period.  The authors used deductive reasoning to form the hypotheses and collect the data necessary to investigate the hypothesis. Additionally, the structure of the paper and the epistemological process is quantitative and based on the scientific method.  The sources used for data gathering have primarily been DefiPulse and their API:s, retrieved using simple python coding and different applications that parse JSON code into the excel format. The transparent nature of blockchain has provided easy access to data needed for this study. Once the data was collected, it was categorized and compiled into an Excel sheet.  Conclusions: It is a considerable result that the ratio of locked ETH to total supply lacks significance for the price of ether, as it is counterintuitive to the macroeconomic theory of demand and supply. Presumably, the locked eth is not to be considered as a corresponding decrease in supply. However, if that was the case, the locked ratio of 10% is considerable and should affect the price as there is less supply available to the market.  In accordance with hypotheses two, three, and four, changes in the price of ether, TVL, and utilization rate affect the price of the native token. A notable distinction between the three different platforms lies in what metrics correlate more strongly with price changes. It for Compound and Aave was TVL, but utilization rate for MakerDAO. What causes these differences between seemingly similar platforms is a subject for further study.

La blockchain propose un système d'enregistrement décentralisé, immuable et transparent. Elle offre un réseau de nœuds sans entité de gouvernance centralisée, ce qui la rend "indéchiffrable" et donc plus sûr que le système d'enregistrement centralisé sur papier ou centralisé telles que les banques. L’approche traditionnelle basée sur l’enregistrement ne fonctionne pas bien avec les relations numériques où les données changent constamment. Contrairement aux canaux traditionnels, régis par des entités centralisées, blockchain offre à ses utilisateurs un certain niveau d'anonymat en leur permettant d'interagir sans divulguer leur identité personnelle et en leur permettant de gagner la confiance sans passer par une entité tierce. En raison des caractéristiques susmentionnées de la blockchain, de plus en plus d'utilisateurs dans le monde sont enclins à effectuer une transaction numérique via blockchain plutôt que par des canaux rudimentaires. Par conséquent, nous devons de toute urgence mieux comprendre comment ces opérations sont gérées par la blockchain et combien de temps cela prend à un nœud du réseau pour confirmer une transaction et l’ajouter au réseau de la blockchain. Dans cette thèse, nous visons à introduire une nouvelle approche qui permettrait d'estimer le temps il faudrait à un nœud de la blockchain Ethereum pour accepter et confirmer une transaction sur un bloc tout en utilisant l'apprentissage automatique. Nous explorons deux des approches les plus fondamentales de l’apprentissage automatique, soit la classification et la régression, afin de déterminer lequel des deux offrirait l’outil le plus efficace pour effectuer la prévision du temps de confirmation dans la blockchain Ethereum. Nous explorons le classificateur Naïve Bayes, le classificateur Random Forest et le classificateur Multilayer Perceptron pour l’approche de la classification. Comme la plupart des transactions sur Ethereum sont confirmées dans le délai de confirmation moyen (15 secondes) de deux confirmations de bloc, nous discutons également des moyens pour résoudre le problème asymétrique du jeu de données rencontré avec l’approche de la classification. Nous visons également à comparer la précision prédictive de deux modèles de régression d’apprentissage automatique, soit le Random Forest Regressor et le Multilayer Perceptron, par rapport à des modèles de régression statistique, précédemment proposés, avec un critère d’évaluation défini, afin de déterminer si l’apprentissage automatique offre un modèle prédictif plus précis que les modèles statistiques conventionnels. / Blockchain offers a decentralized, immutable, transparent system of records. It offers a peer-to-peer network of nodes with no centralised governing entity making it ‘unhackable’ and therefore, more secure than the traditional paper based or centralised system of records like banks etc. While there are certain advantages to the paper based recording approach, it does not work well with digital relationships where the data is in constant flux. Unlike traditional channels, governed by centralized entities, blockchain offers its users a certain level of anonymity by providing capabilities to interact without disclosing their personal identities and allows them to build trust without a third-party governing entity. Due to the aforementioned characteristics of blockchain, more and more users around the globe are inclined towards making a digital transaction via blockchain than via rudimentary channels. Therefore, there is a dire need for us to gain insight on how these transactions are processed by the blockchain and how much time it may take for a peer to confirm a transaction and add it to the blockchain network. In this thesis, we aim to introduce a novel approach that would allow one to estimate the time (in block time or otherwise) it would take for Ethereum Blockchain to accept and confirm a transaction to a block using machine learning. We explore two of the most fundamental machine learning approaches, i.e., Classification and Regression in order to determine which of the two would be more accurate to make confirmation time prediction in the Ethereum blockchain. More specifically, we explore Naïve Bayes classifier, Random Forest classifier and Multilayer Perceptron classifier for the classification approach. Since most transactions in the network are confirmed well within the average confirmation time of two block confirmations or 15 seconds, we also discuss ways to tackle the skewed dataset problem encountered in case of the classification approach. We also aim to compare the predictive accuracy of two machine learning regression models- Random Forest Regressor and Multilayer Perceptron against previously proposed statistical regression models under a set evaluation criterion; the objective is to determine whether machine learning offers a more accurate predictive model than conventional statistical models.

Peer-to-peer (P2P) reputation systems, such as those used by eBay and Amazon, servean important role on the web, especially in E-commerce, as online reputation serves asa primary guiding factor for consumers in making informed decisions. The importanceof these systems, and also the increasing popularity of P2P and distributed systems, theissue of how to prevent and resist sybil and re-entry attacks becomes an important area ofresearch as they can impinge the integrity of those systems. To address this issue, in thisthesis, we propose an approach that encompasses a software architecture and processeswhich serves as a proof-of-concept of how to mitigate sybil and re-entry attacks on review based P2P distributed reputation systems. The architecture uses novel technologiessuch as blockchain, smart contracts, and non-fungible tokens (NFT) in conjunction withSwedish E-id provider BankID to build a sybil and re-entry attack resistant reputationsystem. To validate the feasibility of our approach, we developed a prototype and used itto run experiments to evaluate the functional correctness of the architecture as a mitigation solution

In this dissertation, we address the problem of vagueness in traditional legal contracts by presenting novel methodologies that aid in the paradigm shift from traditional legal contracts to smart contracts. We discuss key enabling technologies that assist in converting the traditional natural language legal contract, which is full of vague words, phrases, and sentences to the blockchain-based precise smart contract, including metrics evaluation during our conversion experiment. To address the challenge of this contract-transformation process, we propose four novel proof-of-concept approaches that take vagueness and different possible interpretations into significant consideration, where we experiment with popular vendors' existing vague legal contracts. We show through experiments that our proposed methodologies are able to study the degree of vagueness in every interpretation and demonstrate which vendor's translated-smart contract can be more accurate, optimized, and have a lesser degree of vagueness. We also incorporated the method of fuzzy logic inside the blockchain-based smart contract, to successfully model the semantics of linguistic expressions. Our experiments and results show that the smart contract with the higher degrees of truth can be very complex technically but more accurate at the same time. By using fuzzy logic inside a smart contract, it becomes easier to solve the problem of contractual ambiguities as well as expedite the process of claiming compensation when implemented in a blockchain-based smart contract.

Globalization has transformed the pharmaceutical industry into a vast, interconnected network. However, this complexity has led to inefficiencies in the supply chain, with existing ERP systems struggling to keep up due to their centralized nature, resulting in a lack of transparency and increased errors. This research proposes efficient distributed ledger-based architectures to address these challenges. In Chapter 3, a new transparent supply chain architecture is introduced to eliminate blind spots and enable stakeholders to verify the authenticity of pharmaceutical products. This system creates a secure, single source of truth for the entire lifecycle of medicines, thereby eliminating counterfeits. Chapter 4 focuses on securing the cold pharmaceutical supply chain using IoT and distributed ledgers. The proposed architecture monitors and controls environmental parameters, ensuring safe drug transport. Scalability is addressed with a novel proof of authentication (PoAh) blockchain called EasyChain. In Chapter 5, the serialization of pharmaceutical products is enhanced through digital twinning, providing an efficient and cost-effective solution while complying with regulations. This research aims to create scalable and efficient pharmaceutical supply chains, reducing counterfeits and improving overall security.

Traditional database with no prior security measures is becoming challenging in the era of data technology. Database storage on a central location with single point of failure and vulnerable to cyber attacks is getting exposed to big risk of being hacked with the evolution of powerful machines and modern hacking techniques. Since its commencement, the BlockChain technology has shown a promising performance for application buildup in diversed fields of life from cryptocurrency to smart contracts and decentralized applications. Although multiple studies on privacy, data confidentiality and security issues of BlockChain are performed but a systematic examination is still needs attention. In this thesis work we conduct a systematic study about the vulnerabilities of BlockChain system and review the security enhancement solutions that may point to a good future direction for further research into the area of BlockChain technology and its applications. Smart contracts are self-executable objects hosted on the 2nd generation blockchain like Ethereum, carry billions of SEK worth of cryptocoins and cannot be updated once deployed. Smart contracts are generally considered secure objects but the systematic analysis of technology and source code exposes a new class of vulnerabilities which are more likely an ethical aspect of programming than the software coding errors. Besides the literature review we empower our results with a static code analysis especially with the perspective of cyber forensics.

A smart contract is a recently emerging technology which enables agreement to be automatable by computers and enforceable by legal enforcement or tamper-proof execution of code. A majority of smart contracts are run on the blockchain which enables smart contract transactions without a central authority. Smart contract implementation contains several challenges which makes implementation more difficult. The problem is that organisations struggle to implement smart contracts due to the absence of documentation, standardisation, and guidelines making it difficult to know how a smart contract should be implemented. Additionally, it is unclear what capabilities and tools are required for smart contract implementation. Therefore, it is challenging for organisations to assess their own competence of smart contract implementation. This thesis aims to develop a Smart Contract Maturity Model (SCMM). The purpose of the model is to clarify the functionalities and capabilities required to implement a smart contract while also offering organisations the ability to assess the smart contract implementation competency. This improves the adoption of smart contracts. Through the help of the design science framework, the SCMM emerged from the thesis. Applying design science included explicating the problem, defining requirements, designing and developing the artefact, demonstrating and evaluating the artefact. A literature survey was used to explicate the problem and to define requirements for the maturity model. Furthermore, a case study including interviews were used to refine the requirements and to demonstrate and evaluate the SCMM. The SCMM includes maturity levels, generic goals and practices, specific goals, key processing areas and practices, tools, glossaries and smart contract examples. Inspired by the Capability Maturity model Model Integration for Development (CMMI-DEV), the maturity levels of the SCMM consisted of initial, foundation, managed, defined, quantitatively managed and optimising. The identified key processing areas were stakeholder capabilities, resources and tools, platform, contract implementation, standards, laws and terminology and security. Although there were several limitations, the SCMM contributed to the field of smart contracts by closing the gap of previous research and improving the adoption of smart contracts.

The ideas and techniques of cryptography and decentralized storage have seen tremendous growth in many industries, as they have been adopted to improve activities in the organization. That called Blockchain technology, it provides an effective transparency solution. Generally, Blockchain has been used for digital currency or cryptocurrency since its inception. One of the best-known Blockchain protocols is Ethereum, which has invented the smart contract to enable Blockchain’s ability to execute a condition, rather than simply acting as storage. Applications that adopt this technology are called ‘Dapps’ or ‘decentralized applications’. However, there are ongoing arguments about synchronization associated with the system. System synchronization is currently extremely important for applications, because the waiting time for a transaction to be verified can cause dissatisfaction in the user experience. Several studies have revealed that privacy leakage occurs, even though the Blockchain provides a degree of security, as a result of the traditional transaction, which requires approval through an intermediate institution. For instance, a bank needs to process transactions via many constitution parties before receiving the final confirmation, which requires the user to wait for a considerable amount of time. This thesis describes the challenge of transaction synchronization between the user and smart contract, as well as the matter of a privacy strategy for the system and compliance. To approach these two challenges, the first task separates different events and evaluates the results compared to an alternative solution. This is done by testing the smart contract to find the best gas price result, which varies over time. In the Ethereum protocol, gas price is one of the best ways to decrease the transaction time to meet user expectations. The gas price is affected by the code structure and the network. In the smart contract, testing is run based on two cases, and solves platform issues such as runners and user experience and reduces costs. It has also been found that collecting the fee before participating in an auction can prevent the problem of runners. The second case aims to prove that freezing the amount of a bid is the best way to increase the user’s experience, and to achieve the better experience of an online auction. The second challenge mainly focuses on the privacy strategy and risk management for the platform, which involves identifying possible solutions for all risk situations, as well as detecting, forecasting and preventing them. Providing strategies, such as securing the smart contract structure, increasing the encryption method in the database, designing a term sheet and agreement, and authorization, help to prevent system vulnerabilities. Therefore, this research aims to improve and investigate an online auction platform by using a Blockchain smart contract to provide evocative user experiences. / Idéer och tekniker för kryptografi och decentraliserad lagring har haft en enorm tillväxt i många branscher, eftersom de har antagits för att förbättra verksamheten i organisationen. Den som kallas Blockchain-tekniken ger den en effektiv transparenslösning. Generellt har Blockchain använts för digital valuta eller cryptocurrency sedan starten. Ett av de mest kända Blockchainprotokollen är Ethereum, som har uppfunnit det smarta kontraktet för att möjliggöra Blockchains förmåga att utföra ett villkor, snarare än att bara fungera som lagring. Applikationer som använder denna teknik kallas 'Dapps' eller 'decentraliserade applikationer'. Det finns emellertid pågående argument om synkronisering associerad med systemet. Systemsynkronisering är för närvarande oerhört viktigt för applikationer, eftersom väntetiden för att en transaktion ska verifieras kan orsaka missnöje i användarupplevelsen. Flera studier har visat att sekretessläckage inträffar, även om Blockchain ger en viss säkerhet, till följd av den traditionella transaktionen, som kräver godkännande genom en mellaninstitution. Till exempel måste en bank bearbeta transaktioner via många konstitutionspartier innan den får den slutliga bekräftelsen, vilket kräver att användaren väntar en betydande tid. Den här avhandlingen beskriver utmaningen med transaktionssynkronisering mellan användaren och smart kontrakt, samt frågan om en sekretessstrategi för systemet och efterlevnad. För att närma sig dessa två utmaningar separerar den första uppgiften olika händelser och utvärderar resultaten jämfört med en alternativ lösning. Detta görs genom att testa det smarta kontraktet för att hitta det bästa gasprisresultatet, som varierar över tiden. I Ethereum-protokollet är gaspriset ett av de bästa sätten att minska transaktionstiden för att möta användarens förväntningar. Gaspriset påverkas av kodstrukturen och nätverket. I det smarta kontraktet körs test baserat på två fall och löser plattformsproblem som löpare och användarupplevelse och minskar kostnaderna. Det har också visat sig att insamlingen av avgiften innan du deltar i en auktion kan förhindra löparproblemet. Det andra fallet syftar till att bevisa att frysning av budbeloppet är det bästa sättet att öka användarens upplevelse och att uppnå en bättre upplevelse av en online auktion. Den andra utmaningen fokuserar huvudsakligen på sekretessstrategin och riskhanteringen för plattformen, som innebär att identifiera möjliga lösningar för alla risksituationer, samt att upptäcka, förutse och förhindra dem. Tillhandahållande av strategier, som att säkra den smarta kontraktsstrukturen, öka krypteringsmetoden i databasen, utforma ett termblad och avtal och godkännande, hjälper till att förhindra systemets sårbarheter. Därför syftar denna forskning till att förbättra och undersöka en online-auktionsplattform genom att använda ett smart avtal med Blockchain för att ge upplevande användarupplevelser.

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In recent years, there have been incidents which decreased people's trust in some organizations and authorities responsible for ratings and accreditation. For a few prominent examples, there was a security breach at Equifax (2017), misconduct was found in the Standard & Poor's Ratings Services (2015), and the Accrediting Council for Independent Colleges and Schools (2022) validated some of the low-performing schools as delivering higher standards than they actually were. A natural solution to these types of issues is to decentralize the relevant trust management processes using blockchain technologies. The research problems which are tackled in this thesis consider the issue of trust in reputation for assessment and review credibility at different angles, in the context of blockchain applications. We first explored the following questions. How can we trust courses in one college to provide students with the type and level of knowledge which is needed in a specific workplace? Micro-accreditation on a blockchain was our solution, including using a peer-review system to determine the rigor of a course (through a consensus). Rigor is the level of difficulty in regard to a student's expected level of knowledge. Currently, we make assumptions about the quality and rigor of what is learned, but this is prone to human bias and misunderstandings. We present a decentralized approach that tracks student records throughout the academic progress at a school and helps to match employers' requirements to students' knowledge. We do this by applying micro-accredited topics and Knowledge Units (KU) defined by NSA's Center of Academic Excellence to courses and assignments. We demonstrate that the system was successful in increasing accuracy of hires through simulated datasets, and that it is efficient, as well as scalable. Another problem is how can we trust that the peer reviews are honest and reflect an accurate rigor score? Assigning reputation to peers is a natural method to ensure correctness of these assessments. The reputation of the peers providing rigor scores needs to be taken into account for an overall rigor of a course, its topics, and its tasks. Specifically, those with a higher reputation should have more influence on the total score. Hence, we focused on how a peer's reputation is managed. We explored decentralized reputation management for the peers, choosing a decentralized marketplace as a sample application. We presented an approach to ensuring review credibility, which is a particular aspect of trust in reviews and reputation of the parties who provide them. We use a Proof-of-Stake based Algorand system as a base of our implementation, since this system is open-source, and it has a rich community support. Specifically, we directly map reputation to stake, which allows us to deploy Algorand at the blockchain layer. Reviews are analyzed by the proposed evaluation component using Natural Language Processing (NLP). In our system, NLP gauges the positivity of the written review, compares that value to a scaled numerical rating given, and determines adjustments to a peer's reputation from that result. We demonstrate that this architecture ensures credible and trustworthy assessments. It also efficiently manages the reputation of the peers, while keeping reasonable consensus times. We then turned our focus on ensuring that a peer's reputation is credible. This led us to introducing a new type of consensus called "Proof-of-Review". Our proposed implementation is again based on Algorand, since its modular architecture allows for easy modifications, such as adding extra components, but this time, we modified the engine. The proposed model then provides a trust in evaluations (review and assessment credibility) and in those who provide them (reputation credibility) using a blockchain. We introduce a blacklisting component, which prevents malicious nodes from participating in the protocol, and a minimum-reputation component, which limits the influence of under-performing users. Our results showed that the proposed blockchain system maintains liveliness and completeness. Specifically, blacklisting and the minimum-reputation requirement (when properly tuned) do not affect these properties. We note that the Proof-of-Review concept can be deployed in other types of applications with similar needs of trust in assessments and the players providing them, such as sensor arrays, autonomous car groups (caravans), marketplaces, and more.