Stefanos Chaliasos, Denis Firsov, Benjamin Livshits
Blockchains like Bitcoin and Ethereum have revolutionized digital transactions, yet scalability issues persist. Layer 2 solutions, such as validity proof Rollups (ZK-Rollups), aim to address these challenges by processing transactions off-chain and validating them on the main chain. However, concerns remain about security and censorship resistance, particularly regarding centralized control in Layer 2 and inadequate mechanisms for enforcing these properties through Layer 1 smart contracts. In their current form, L2s are susceptible to multisig attacks that can lead to total user funds loss. This work presents a formal analysis using the Alloy specification language to examine and design key Layer 2 functionalities, including forced transaction queues, safe blacklisting, and upgradeability. Through this analysis, we identify pitfalls in existing designs and introduce an enhanced model that has been model-checked to be correct. Finally, we propose a complete end-to-end methodology to analyze rollups' security and censorship resistance based on manually translating Alloy properties to property-based testing invariants, setting new standards.
Risk and uncertainty are crucial factors in decision-making processes, especially when integrating emerging technologies into essential systems like supply chains. Failing to adequately consider significant risks can disrupt supply chain operations, leading to a loss of competitive edge and causing financial and reputational damage. On the other hand, the complex nature of new technology environments, differing viewpoints among stakeholders, and the challenges of interpreting data introduce a variety of uncertainties in decision-making. In this study, we conduct a thorough examination of how blockchain strategies can be applied within supply chain frameworks. Our analysis utilizes data-driven network decision-making models that are refined to effectively manage uncertainty and risk. These models take into account aspects such as supply chain dynamics and technological factors. Importantly, we meld risk considerations with our models to tackle efficiency shortfalls, while also accounting for uncertainty caused by ambiguous and stochastic data environments. By applying and assessing these models in a real-world case study of the oil and gas industry, our research uncovers insightful observations. Specifically, we find that adopting a localization strategy presents specific risks, while a single-use strategy yields significant efficiency improvements.
Aman Dwivedi, Divyansh Sharma, Sharad Gumber, Satyam Gupta
Abstract: Carpooling has seen a significant upsurge in popularity in recent years since it relieves commuters of the burden of driving a car and later spares them from the mad dash to locate a parking space. The industry now uses centralised database servers, which puts the system at risk of hacking, causes data leaks, and undermines security within the system. Additionally, there is a chance that the owner will misuse the data in a centralised system. Since the newly developed Blockchain technology provides complete anonymity and database transparency, data security and traceability may be guaranteed across the entire server. The goal of the suggested solution is to create and implement a blockchain-based, smart contract-based peer-to-peer vehicle sharing system. The Solidity programming language is utilised to carry out the smart contracts. Ethereum blockchain is used in the ecosystem's construction. Eliminating the middleman would result in a peer-to- peer (P2P) car-sharing programme, which would reflect decreased costs and exposure to data theft.
Krzysztof Gogol, Johnnatan Messias, Deborah Miori, Claudio J. Tessone · 5 authors
This study quantifies the potential non-atomic MEV on Layer-2 (L2) blockchains by measuring the arbitrage opportunities between cross-rollup and DEX-CEX. Over recent years, we observe a shift in trading activities from Ethereum to rollups, with swaps on rollups occurring 2-3 times more frequently, albeit with lower trade volumes. By analyzing the costs of swap on L2s and price discrepancies cross-rollup and DEX-CEX, we identify more than 500 000 unexplored arbitrage opportunities. In particular, we find that these opportunities persist, on average, for 10 to 20 blocks, necessitating the modification of the Loss Versus Rebalancing (LVR) metric to prevent double-counting. Our findings indicate that the arbitrage opportunities in Arbitrum, Base, and Optimism range between 0.03% and 0.05% of the trading volume, while in the ZKsync it fluctuates around 0.25%.
Srisht Fateh Singh, Panagiotis Michalopoulos, Andreas Veneris
This paper introduces BAKUP, a smart contract insurance design for decentralized finance users to mitigate risks arising from platform vulnerabilities. While providing automated claim payout, BAKUP utilizes a modular structure to harmonize three key features: the platform's resilience against vulnerabilities, the flexibility of underwritten policies, and capital efficiency. An immutable core module performs capital accounting while ensuring robustness against external vulnerabilities, a customizable oracle module enables the underwriting of novel policies, and an optional and peripheral yield module allows users to independently manage additional yield. The implementation incorporates binary conditional tokens that are tradable on automated market maker (AMM)-based exchanges. Finally, the paper examines specific liquidity provision strategies for the conditional tokens, demonstrating that a conservative strategy and parameterization can effectively reduce the divergence loss of liquidity providers by more than 47 % compared to a naive strategy in the worst-case scenario.
The visitor economy is responsible for a substantial percentage of the global carbon footprint. The mechanisms used to decarbonize it are insufficient, and the industry is relying on carbon trading with substandard credits that allow businesses to outsource the responsibility to decarbonize. We aim to transform carbon markets, help finance climate investments, and support decarbonization strategies. We identify and define the problem, outline the components and their interactions, and develop a conceptual model to transform carbon markets. The new, blockchain-based Carbon Tokenomics Model rolls out a decentralized database to store, trade, and manage carbon credits, with the goal of enabling sustainable climate finance investment. We outline the criteria needed for an industry-wide carbon calculator. We explain the process needed to increase rigor in climate investments in the visitor economy and introduce a delegated Proof of Commitment consensus mechanism. Our inclusive and transparent model illustrates how to reduce transaction costs and how to build consumer and industry trust, generating much-needed investments for decarbonization.
Proof-of-stake (PoS) has emerged as a natural alternative to the resource-intensive Proof-of-Work (PoW) blockchain, as was recently seen with the Ethereum Merge. PoS-based blockchains require an initial stake distribution among the participants. Typically, this initial stake distribution is called bootstrapping. This paper argues that existing bootstrapping protocols are prone to centralization. To address centralization due to bootstrapping, we propose a novel game $Γ_\textsf{bootstrap}$. Next, we define three conditions: (i) Individual Rationality (IR), (ii) Incentive Compatibility (IC), and (iii) $(τ,δ,ε)-$ Decentralization that an \emph{ideal} bootstrapping protocol must satisfy. $(τ,δ,ε)$ are certain parameters to quantify decentralization. Towards this, we propose a novel centralization metric, C-NORM, to measure centralization in a PoS System. We define a centralization game -- $Γ_\textsf{cent}$, to analyze the efficacy of centralization metrics. We show that C-NORM effectively captures centralization in the presence of strategic players capable of launching Sybil attacks. With C-NORM, we analyze popular bootstrapping protocols such as Airdrop and Proof-of-Burn (PoB) and prove that they do not satisfy IC and IR, respectively. Motivated by the Ethereum Merge, we study W2SB (a PoW-based bootstrapping protocol) and prove it is ideal. In addition, we conduct synthetic simulations to empirically validate that W2SB bootstrapped PoS is decentralized.
Zero-knowledge proofs (ZKPs) are computationally demanding to generate. Their importance for applications like ZK-Rollups has prompted some to outsource ZKP generation to a market of specialized provers. However, existing market designs either do not fit the ZKP setting or lack formal description and analysis. In this work, we propose a formal ZKP market model that captures the interactions between users submitting ZKP tasks and provers competing to generate proofs. Building on this model, we introduce $Prooφ$, an auction-based ZKP market mechanism. We prove that $Prooφ$ is incentive compatible for users and provers, and budget balanced. We augment $Prooφ$ with system-level designs to address the practical challenges of our setting, such as Sybil attacks, misreporting of prover capacity, and collusion. We analyze our system-level designs and show how they can mitigate the various security concerns.
The Internet of Vehicles (IoV) has a significant impact on improving traffic efficiency and driving safety. In this paper, we propose an intelligent transportation credit system based on blockchain, and design a crossroad passing smart contract that allows time-sensitive convoys to pass a crossroad earlier by paying traffic tokens for right-of-way trade. Second, this paper formulates the time–cost optimization problem under the premise of protecting the privacy of preceding convoys. Based on game theory with incomplete information, two right-of-way optimal bid strategies are given. Both theoretical analysis and simulation prove that the strategy proposed in this paper effectively reduces the waiting time of time-sensitive vehicles at a crossroad and increases the trade success probability, which, in turn, improves the expected total profit of convoys and achieves Pareto improvement.
Shovon Das Chowdhury, Tanjil Ahmed, Ruhul Amin, Rahat Ahmed Chowdhury · 6 authors
The escalating growth in population has led to a substantial increase in both private and public transportation on roads. Consequently, the surge in accidents, traffic rule violations, and other traffic-related offenses has become a daily concern. Addressing these issues is crucial for ensuring the safety of passengers and enhancing transparency in driver recruitment, especially when considering violations that may have occurred abroad. This paper introduces S- DrivingRecords, focusing on pivotal functionalities such as the registration of cases related to traffic rule violations or accidents, case withdrawal, and the sharing of driver history with external Decentralized Applications (DApps). The system facilitates case registration through a dedicated traffic DApp, enabling drivers to share their records with other entities, be they companies or individuals. This feature allows individuals to conduct thorough checks on a driver's history before making decisions such as hiring or booking. The implementation employs Hyperledger Fabric as a distributed ledger to ensure the security of data, while the use of Hyperledger Cacti facilitates seamless collaboration with different systems.
As the potential of directed acyclic graph (DAG)-based distributed ledgers in IoT systems unfolds, a need arises to understand their intricate dynamics in real-world scenarios. It is well known that discrete event simulations can provide high-fidelity evaluations of protocols. However, there is a lack of public discrete event simulators capable of assessing DAG-based distributed ledgers. In this paper, a discrete-event-based distributed ledger simulator is introduced, with which we investigate a custom Python-based implementation of IOTA's Tangle DAG protocol. The study reveals the dynamics of Tangle (particularly Poisson processes in transaction dynamics), the efficiency and intricacies of the random walk in Tangle, and the quantitative assessment of node convergence. Furthermore, the research underscores the significance of weight updates without depth limitations and provides insights into the role, challenges, and implications of the coordinator/validator in DAG architectures. The results are striking, and although the findings are reported only for Tangle, they demonstrate the need for adaptable and versatile discrete event simulators for DAG architectures and tip selection methodologies in general.
Public permissionless blockchains facilitate peer-to-peer digital transactions, yet face performance challenges, specifically minimizing transaction confirmation time to decrease energy and time consumption per transaction. Performance evaluation and prediction is crucial in achieving this objective, with performance modeling as a key solution despite the complexities involved in assessing these blockchains. This survey examines prior research concerning the systems used to model blockchain performance, specifically focusing on public permissionless blockchains. Initially, it provides foundational knowledge about these blockchains and the crucial performance parameters for their assessment. Additionally, the study delves into research on the performance modeling of public permissionless blockchains, predominantly considering these systems as bulk service queues. It also examines prior studies on workload and traffic modeling, characterization, and analysis within these blockchain networks. By analyzing existing research, our survey aims to provide insights and recommendations for researchers keen on enhancing the performance of public permissionless blockchains or devising novel mechanisms in this domain.
With the development of Electric Vehicles (EVs), Vehicle-to-Vehicle (V2V) electricity transactions have gained popularity. Among them, EV users can easily obtain information such as their own location and speed through the Internet of Vehicles (IoV), and communicate with other entities through the IoV, but the leak of the electricity transaction plan and private information such as identity, location, speed, etc. required for the transaction may put the users in danger and undermine the fairness of the transaction. Aiming at the above problems, A V2V electricity transaction scheme with privacy protection based on the IoV and consortium blockchain is proposed. Firstly, a long-term and short-term pseudo-identity algorithm is designed for users participating in V2V transactions. Users conduct each electricity transaction with different short-term pseudo-identities to prevent the leakage of their identity information; and when fraudulent transactions occur, the real identity of the fraudulent users can be traced based on their long-term pseudo-identities or public key information. Secondly, a certificateless aggregate signcryption algorithm is designed for secure communication in the IoV. Finally, consortium blockchain technology is adopted to solve the problems of single point of failure and data tampering that exist in centralized transactions. At the same time, a reputation value evaluation mechanism based on transaction completion rate and a Proof of Reputation consensus mechanism based on fixed time and fixed block capacity packing method are also designed, which not only reduces the computational power consumption but also motivates the seller EV to conduct V2V electricity transactions in good faith. The theory proves that the scheme is capable of protecting the privacy of EV users effectively. The performance evaluations demonstrate that this scheme has low communication overhead and the computational overhead also has certain advantages.
Yuxiao Liang, Zhishang Wang, Abderazek Ben Abdallah
In the present era, energy issues are a significant concern, and the energy trading market is the crucial sector to facilitate supply-demand balance and sustainable development. For better demand response and grid balancing, vehicle-to-grid (V2G) technology is rapidly gaining importance in energy markets. To narrow the gap between ideal V2G goals and actual applications needs, energy trading system has to overcome the challenges of over-centralized structure, inflexible timeline adaptation, limited market scale and energy efficiency, excessive feedback time costs, and low rate of economic return. To address these issues and ensure a secure energy market, we propose a decentralized intelligent V2G system called V2G Forecasting and Trading Network (V2GFTN) to achieve efficient and robust energy trading in campus EV networks. A multiple blockchain structure is proposed in V2GFTN to ensure trading security and data privacy between energy requests and offers. V2GFTN also integrates energy forecasting functions for EVs with a smart energy trading and EV allocation mechanism called SRET so that the EVs with driving tasks can supply their extra power back to the grid and achieve higher energy efficiency and economic profit. Through rigorous experimentation and compared with equivalent studies, V2GFTN system has demonstrated higher economic profit and energy demand fill rate by up to 1.6 times and 1.9 times than the state-of-the-art V2G approaches.
Michael Lustenberger, Sabrina Wollenschläger, Lukas Küng
This paper explores the promise of decentralized autonomous organizations (DAOs) as a digital governance tool for collaborative housing initiatives. Based on existing literature around the collaborative housing initiative no1s1, we explore the research question: How can DAOs help govern collaborative housing initiatives? To address this, we employ conceptual research methods, synthesizing theories from the field of collaborative housing and DAOs to propose a new framework for the governance of such initiatives. Our analysis identifies five key benefits of DAOs in collaborative housing governance: a transparent crypto-accounting system, scalable decision-making, global jurisdiction and rule enforcement, automated rights and incentives system, and flexible polycentric governance. These benefits align with Elinor Ostrom’s “Governing the Commons” principles and highlight the potential of DAOs to enable scalability and autonomy in geographically dispersed communities. While theoretical, our study provides insights into the transformative potential of blockchain-based DAOs in collaborative housing governance, laying the groundwork for further research and real-world and empirical validation.
In today’s world, where digital technologies play an increasingly important role in various aspects of life, protecting data and ensuring its confidentiality and integrity is becoming an increasingly urgent task. This problem is especially important in the context of state registers, which contain a large volume of valuable information about citizens, businesses and other entities. Delimiting access to public registers is a key task for ensuring security, transparency and efficiency of data management in government bodies. In this context, the use of Non-Fungible Tokens (NFT) and blockchain technology can be a promising solution. This article examines the possibilities of using NFTs and blockchain to delimit access to public registries in Ukraine. This paper defines key concepts such as NFT, blockchain, identification, authentication, and access control and examines their possible applications for delimiting access to public registries. It also describes how the use of blockchain and NFT technologies can be a key solution for ensuring the security and efficiency of public registry management. Blockchain, as a distributed database, provides reliable storage of transaction history and impenetrable encryption of data. Each block in the chain has a unique hash that links it to the previous block, making any attempt to change the data in the blocks nearly impossible without detection. On the other hand, Non-Fungible Tokens (NFT) can serve as unique digital identifiers that define access rights to specific data in public registries. Each NFT contains a unique digital signature that confirms its ownership and characteristics, and can be used to precisely define access rights to specific data or resources. Together, these technologies can create a reliable and secure infrastructure for managing public registries, ensuring transparency, privacy and irreversibility of transactions.
Nebojša Horvat, Dušan Gajić, Petar Trifunović, Veljko Petrović · 6 authors
Distributed ledger technology (DLT) and blockchain-based energy trading solutions are often labeled as resource-hungry, excessive power consumers which consequently create a significant carbon footprint. Using this approach to energy trading, without simultaneously minimizing energy consumption, defeats the purpose of using such trading solutions to encourage renewable energy production and may even cancel out any ecological benefits. This paper demonstrates that it is possible to create a DLT-based energy trading system which provides security, transparency, autonomy, scalability, and decentralization, provided by using a DLT, but with significantly lower penalties than other previously known solutions. This is best illustrated through the fact that the carbon footprint per transaction of the solution presented in this paper is 0.19 grams of$CO_{2}$compared to 20 grams of$CO_{2}$created by single transaction of similar complexity on the Ethereum blockchain. This makes per-transaction carbon footprint of our system approximate 100 times smaller than that of the most commonly used Ethereum blockchain. We present the architecture and features of the proposed platform, as well as a thorough analysis of its performance, including power consumption and estimated carbon footprint. All experiments are done on a dedicated Beowulf cluster comprised of general-purpose computers. The cluster mimics a microgrid environment and presents a testing ground for real-world performance and power consumption analysis of a system used for trading energy predominantly produced from prosumers and their renewable sources.
Yi-Jen Su, Chao-Ho Chen, Tsong-Yi Chen, Chun-Wei Yeah
The main causes for the risks of used-car trading lie in the information asymmetry between buyers and sellers and the absence of a trust mechanism. This study proposed applying the Ethereum blockchain and InterPlanetary File System (IPFS) to construct a used-car trading and management information system that supports decentralized data storage services. This mechanism could support the permanent storage, immutability, and traceability of car maintenance data through the operation of smart contracts. Furthermore, car information is stored and managed by IPFS. Slither monitors the security of this system by detecting security bugs in the operation of smart contracts.
Blockchain technology has become a powerful disruptive force that upends established ideas in several industries. A fascinating point of convergence is that of blockchain technology and Business Process Management (BPM), where the distributed and immutable characteristics of blockchain promise to completely transform the modeling, implementation, and oversight of business processes. This symbiosis offers a singular chance to develop corporate processes that are more efficient, safe, and transparent. Nevertheless, to guarantee that blockchain-specific components are accurately represented in these processes, modeling techniques need to be critically examined as part of integrating blockchain into BPM. This literature review examines blockchain-BPM integration using different modeling methodologies. Though well-established, traditional BPM approaches may need help with blockchain-specific aspects. Blockchain-oriented modeling includes smart contracts and decentralized consensus. Hybrid models with blockchain and traditional elements are popular. Adaptability, model clarity, and blockchain integration are evaluated in the analysis. This literature review aims to improve corporate processes’ efficiency, security, and transparency by investigating how to model the integration of blockchain and BPM better.
Rabia Khan, Amjad Mehmood, Carsten Maple, Kevin Curran · 5 authors
Strategic investment(s) in vehicle automation technologies led to the rapid development of technology that revolutionised transport services and reduced fatalities on a scale never seen before. Technological advancements and their integration in Connected Autonomous Vehicles (CAVs) increased uptake and adoption and pushed firmly for the development of highly supportive legal and regulatory and testing environments. However, systemic threats to the security and privacy of technologies and lack of data transparency have created a dynamic threat landscape within which the establishment and verification of security and privacy requirements proved to be an arduous task. In CAVs security and privacy issues can affect the resilience of these systems and hinder the safety of the passengers. Existing research efforts have been placed to investigate the security issues in CAVs and propose solutions across the whole spectrum of cyber resilience. This paper examines the state-of-the-art in security and privacy solutions for CAVs. It investigates their integration challenges, drawbacks and efficiencies when coupled with distributed technologies such as Blockchain. It has also listed different cyber-attacks being investigated while designing security and privacy mechanism for CAVs.
The collaborative path planning and scheduling can overcome the limitations of single vehicle intelligence to obtain a globally optimal decision strategy in cognitive internet of vehicles (CIoVs). The collaboration of vehicles necessitates the exchange of environmental and decision information, generating massive collaborative computing tasks with strict latency requirements. Leveraging mobile edge computing (MEC) technology, computing tasks can be processed near the vehicles to reduce latency. However, traffic congestion and computational load imbalance seriously affect traffic efficiency and computational latency. In hybrid driving scenarios, it is challenging to fulfill the diverse service requirements of vehicles with different intelligence levels. Moreover, non-collaborative tend to result in traffic congestion due to vehicle aggregation effects, while centralized solutions lack flexibility and have high computational complexity. To address these concerns, a distributed multi-agent reinforcement learning (DMARL) algorithm is proposed for collaborative path planning and scheduling in a blockchain-based collaboration framework. In this framework, we model the communication, traffic situation and task processing of the system and formulate a joint optimization problem to minimize both travel time and computation latency. Last, we convert the scheduling problem for different types of vehicles into Markov decision processes (MDPs) and propose Q-learning-based DMARL algorithm to achieve proactive load balancing of both road infrastructures and MEC nodes (MECNs). Simulation results demonstrate that the proposed approach outperforms the comparison schemes in terms of load balance indexes of roads and MECNs, travel time, and computation latency.