This study introduces De-DSI, a novel framework that fuses large language models (LLMs) with genuine decentralization for information retrieval, particularly employing the differentiable search index (DSI) concept in a decentralized setting. Focused on efficiently connecting novel user queries with document identifiers without direct document access, De-DSI operates solely on query-docid pairs. To enhance scalability, an ensemble of DSI models is introduced, where the dataset is partitioned into smaller shards for individual model training. This approach not only maintains accuracy by reducing the number of data each model needs to handle but also facilitates scalability by aggregating outcomes from multiple models. This aggregation uses a beam search to identify top docids and applies a softmax function for score normalization, selecting documents with the highest scores for retrieval. The decentralized implementation demonstrates that retrieval success is comparable to centralized methods, with the added benefit of the possibility of distributing computational complexity across the network. This setup also allows for the retrieval of multimedia items through magnet links, eliminating the need for platforms or intermediaries.

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With the proliferation of Internet of Things (IoT) ecosystems, traditional resource orchestration mechanisms, executed on fog devices, encounter significant scalability, reliability and security challenges. To tackle these challenges, recent decentralized algorithms in Fog-IoT use Distributed Ledger Technologies to orchestrate resources and payments between peers. However, while distributed ledgers provide many desirable properties, their consensus mechanism introduces a performance bottleneck. This paper introduces Light-HIDRA, a consensus-less and decentralized resource orchestration system for Fog-IoT environments. At its core, Light-HIDRA uses Byzantine Reliable Broadcast (BRB) to coordinate actions without centralized control, therefore drastically reducing communication overhead and latency compared to consensus-based solutions. Light-HIDRA coordinates the scheduling and execution of workloads, and securely manages the payments that peers receive for dedicating resources to workloads. Light-HIDRA further increases performance and reduces overhead by grouping peers into distinct domains. We conduct an in-depth analysis of the protocol’s security properties, investigating its efficiency and robustness in diverse situations. We evaluate the performance of Light-HIDRA, highlighting its performance over HIDRA, a state-of-the-art baseline that uses smart contracts. Our experiments demonstrate that Light-HIDRA reduces the bandwidth usage by up to 57x, the latency of workload offloading by up to 142x, and shows superior throughput compared to HIDRA.@en

Shared code in blockchains, known as smart contracts, stands to replace important parts of our digital governance and financial infrastructure. The permissionless execution of smart contracts is tightly coupled to cryptocurrencies and Proof-of-Work blockchains. As a result, smart contracts inherit the environmental impact of Proof-of-Work blockchains, like its energy consumption, carbon footprint, and electronic waste. The four concepts of relaxed consistency, strong identities, probabilistic consensus, and the use of liabilities instead of assets may change the status quo. This work explores the integration of these concepts to decouple smart contracts from Proof-of-Work blockchains. By means of a local-first approach, that may expose users to inconsistent ephemeral contract states, the architecture of smart contracts can be transformed to become green. Because such contract states may be dropped, we base the interactions between users on liabilities. We propose a novel paradigm for smart contract architectures, named Green Smart Contracts, that is based on a local-first approach. Furthermore, we present and implement a prototype solution for this paradigm. We validate the need for a mechanism to resolve consistency violations by replaying the contract calls of a real smart contract. Our simulation shows that violations occur more often (13\% of contract invocations) when using liabilities than when using a traditional blockchain (3\% of contract invocations). However, we additionally validate that they can be avoided using a consensus mechanism, and our experiments show that a publish-subscribe messaging pattern uses the fewest messages to do so, though it may not be applicable for use cases that disallow the inherent imbalance in the messaging between peers. Our carbon emission estimation shows that a Green Smart Contract approach lowers carbon emissions by 52.31\% when compared to the messaging behavior of a typical peer-to-peer blockchain with 1000 nodes.@en

The popularity of blockchain technology has bootstrapped many “Web3” applications, e.g., Ethereum and IPFS, that apply distributed ledger technology to store transactions. The amount of transactions generated and stored in such Web3 applications is significant and, in its raw form, usually not searchable by users. Existing Web3 transaction indexing and search engines are predominantly centralized and, therefore, can manipulate search results or censor particular queries. With the proliferation of Web3 transactions and applications, a decentralized and censorship-resistant search primitive is becoming essential. We present DESCAN, a decentralized and censorship-resistant indexing and search engine for Web3. Users index their local Web3 transactions using custom rules that output triplets. Generated triplets are bundled in a distributed transaction graph that is searchable by other users. To coordinate search and distribute the storage of the transaction graph over peers in the network, we build upon a Skip Graph (SG) data structure. Since the Skip Graph does not provide any resilience against adversarial peers that censor searches, we propose four modifications to improve its robustness. We implement DESCAN and conduct experiments with up to 12 800 peers and 10 million Ethereum transactions. Our experiments show that DESCAN with our modifications enabled can tolerate 20% adversarial peers and 35% unresponsive peers without disruption. Moreover, we find that searches in DESCAN are usually completed well within a second, even when the network grows. Finally, we show that storage and network costs are evenly distributed amongst peers as the network grows.

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Catalyzed by the popularity of blockchain technology, there has recently been a renewed interest in the design, implementation and evaluation of decentralized systems. Most of these systems are intended to be deployed at scale and in heterogeneous environments with real users and unpredictable workloads. Nevertheless, most research in this field evaluates such systems in controlled environments that poorly reflect the complex conditions of real-world environments. In this work, we argue that deployment is crucial to understanding decentralized mechanisms in a real-world environment and an enabler to building more robust and sustainable systems. We highlight the merits of deployment by comparing this approach with other experimental setups and show how our lab applied a deployment-first methodology. We then outline how we use Tribler, our peer-to-peer file-sharing application, to deploy and monitor decentralized mechanisms at scale. We illustrate the application of our methodology by describing a deployment trial in experimental tokenomics. Finally, we summarize four lessons learned from multiple deployment trials where we applied our methodology.@en

Manipulation of user transactions by miners in permissionless blockchain systems is a growing concern. This problem is a pervasive and systemic issue that incurs high costs for users of decentralised applications and is known as Miner Extractable Value (MEV). Furthermore, transaction manipulations create other issues such as congestion, higher fees, and system instability. Detecting transaction manipulations is difficult, even though it is known that they originate from the pre-consensus phase of transaction selection for building blocks, at the base layer of blockchain protocols. In this paper, we summarize known transaction manipulation attacks. We present LO, an accountable base layer protocol designed to detect and mitigate transaction manipulations. LO is built around the accurate detection of transaction manipulations and assignment of blame at the granularity of a single mining node. LO forces miners to log all the transactions they receive into a secure mempool data structure and to process them in a verifiable manner. Overall, LO quickly and efficiently detects censorship, injection or re-ordering attempts. Our performance evaluation shows that LO is also practical and only introduces a marginal performance overhead.

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Web3 is emerging as the new Internet-interaction model that facilitates direct collaboration between strangers without a need for prior trust between network participants and without central authorities. However, one of its shortcomings is the lack of a defense mechanism against the ability of a single user to generate a surplus of identities, known as the Sybil attack. Web3 has a Sybil attack problem because it uses peer sampling to establish connections between users. We evaluate the promising but under-explored direction of Sybil avoidance using network latency measurements, according to which two identities with equal latencies are suspected to be operated from the same node, and thus are likely Sybils. Network latency measurements have two desirable properties: they are only malleable by attackers by adding latency, and they do not require any trust between network participants. Our basic SybilSys mechanism avoids Sybil attackers using only network latency measurements if attackers do not actively exploit their malleability. We present an enhanced version of SybilSys that protects against targeted attacks using a variant of the flow correlation attack, which we name TrafficJamTrigger. We show how the message flows of Round-Trip Time measurements can be used to expose attack patterns and we propose and evaluate six classifiers to recognize these patterns. Our experiments show, through both emulation and real-world deployment, that enhanced SybilSys can serve a fundamental role for Web3, effectively establishing connections to real users even in the face of networks consisting of 99% Sybils.@en

Self-Sovereign Identity (SSI) aspires to create a standardised identity layer for the Internet by placing citizens at the centre of their data, thereby weakening the grip of big tech on current digital identities. However, as millions of both physical and digital identities are lost annually, it is also necessary for SSIs to possibly be revoked to prevent misuse. Previous attempts at designing a revocation mechanism typically violate the principles of SSI by relying on central trusted components. This lack of a distributed revocation mechanism hampers the development of SSI. In this paper, we address this limitation and present the first fully distributed SSI revocation mechanism that does not rely on specialised trusted nodes. Our novel gossip-based propagation algorithm disseminates revocations throughout the network and provides nodes with a proof of revocation that enables offline verification of revocations. We demonstrate through simulations that our protocol adequately scales to national levels.@en

Decentralised Autonomous Organisations (DAOs) have the capability of being a disruptive Web3 technology. Their usage of cryptographically secure distributed ledgers shows promise of replacing existing technical and financial intermediaries. However, this promise has not been fully materialised yet: existing attempts typically rely on centralisation as the required decentralised components do not exist or are not mature enough. We present our Web3 Deployment Experiment around a robust decentralised economy to address these issues. Our economy is unique due to the removal of all centralised components and governance. It is resilient against legal and economic attacks as no individual or organisation can compromise its functioning. We dub this characteristic extreme decentralisation. Similar to BitTorrent and Bitcoin, our extreme decentralisation DAOs carefully avoid single points of failure and are effectively unstoppable. Within our experiment around a music economy, we bypass all intermediaries in finance, technology, and the music industry itself with a direct donation to musicians. We demonstrate the viability of collective decision-making within our decentralised economy and present a set of principles for Web3 DAOs. Our implementation shows that the DAO ecosystem is fully deployable on smartphones, allowing anyone to create a DAO without reliance on central authorities or components.

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Web3 networks are emerging to replace centrally-governed networking infrastructure. The integrity of the shared public infrastructure of Web3 networks is guaranteed through data sharing between nodes. However, due to the unstructured and highly partitioned nature of Web3 networks, data sharing between nodes in different partitions is a challenging task. In this paper we present the TSRP mechanism, which approaches the data sharing problem through nodes auditing each other to enforce carrying of data between partitions. Reputation is used as an analogue for the likelihood of nodes interacting with nodes from other partitions in the future. The number of copies of data shared with other nodes is inversely related to the nodes’ reputation. We use a real-world trace of Twitter to show how our implementation can converge to an equal number of copies as structured approaches@en

The growing number of implementations of blockchain systems stands in stark contrast with still limited research on a systematic comparison of performance characteristics of these solutions. Such research is crucial for evaluating fundamental trade-offs introduced by novel consensus protocols and their implementations. These performance limitations are commonly analyzed with ad-hoc benchmarking frameworks focused on the consensus algorithm of blockchain systems. However, comparative evaluations of design choices require macro-benchmarks for uniform and comprehensive performance evaluations of blockchains at the system level rather than performance metrics of isolated components. To address this research gap, we implement Gromit, a generic framework for analyzing blockchain systems. Gromit treats each system under test as a transaction fabric where clients issue transactions to validators. We use Gromit to conduct the largest blockchain study to date, involving seven representative systems with varying consensus models. We determine the peak performance of these systems with a synthetic workload in terms of transaction throughput and scalability and show that transaction throughput does not scale with the number of validators. We explore how robust the subjected systems are against network delays and reveal that the performance of permissoned blockchain is highly sensitive to network conditions.@en

The landscape of electronic marketplaces has been monopolized by a handful of market operators that have accumulated tremendous power during the last decades. This trend raises concerns about fairness and market manipulation by these operators acting as gatekeepers. These concerns have recently been outlined in the EU Digital Markets Act (DMA). In this work, we highlight how technological logic of separation understood in the framework of decentralization can address manipulation concerns. As a first step, we devise a reference model of electronic marketplaces, containing six functional components, and outline how control over these components enables different manipulative practices by gatekeepers. We identify two dimensions of decentralization that can counterbalance monopolistic abuse of marketplace components. We then present a software implementation of our reference model and demonstrate how decentralization and unbundling of market components can alleviate manipulation and fairness concerns. We end our work with a review of related approaches and conclude that modular and interoperable marketplaces can enable an open ecosystem of fair electronic markets envisioned by the DMA.

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Decentralized reputation schemes present a promising area of experimentation in blockchain applications. These solutions aim to overcome the shortcomings of simple monetary incentive mechanisms of naive tokenomics. However, there is a significant research gap regarding the limitations and benefits of such solutions. We formulate these trade-offs as a conjecture on the irreconcilability of three desirable properties of the reputation system in this context. Such a system can not be simultaneously generalizable, trustless, and Sybil resistant. To handle the limitations of this trilemma, we propose MeritRank: Sybil tolerant feedback aggregation mechanism for reputation. Instead of preventing Sybil attacks, our approach successfully bounds the benefits of these attacks. Using a dataset of participants’ interactions in MakerDAO, we run experiments to demonstrate Sybil tolerance of MeritRank. Decay parameters of reputation in MeritRank: transitivity decay and connectivity decay, allow for a fine-tuning of desirable levels of reputation utility and Sybil tolerance in different use contexts.@en

Permissioned blockchains are increasingly being used as a solution to record transactions between companies. Several use cases that leverage permissioned blockchains focus on the representation and management of real-world assets. Since the number of incompatible blockchains is quickly growing, there is an increasing need for a universal mechanism to exchange, or trade, digital assets between these isolated platforms. There currently is no universal mechanism for inter-blockchain asset exchange without a requirement for trusted authorities that coordinate the trade. We address this shortcoming and present XChange, a universal mechanism for asset exchange between permissioned blockchains. To achieve universality and to avoid trusted authorities that coordinate a trade, XChange does not provide atomic guarantees but leverages risk mitigation strategies to reduce value at stake. Our mechanism records the specifications and progression of each trade within records on a distributed log. XChange reduces the economic gains of adversaries by bounding the total amount of fraud they can commit at any time. After having committed fraud, an adversary is forced to finish its ongoing trades before it can engage in new trades. We first present a four-phased protocol that coordinates an asset exchange between two traders. We then outline how trade records can be stored on TrustChain, which is a lightweight distributed ledger specifically built for the tamper-proof storage of data elements. We implement XChange and conduct experiments. Our experiments demonstrate that XChange is capable of reducing the economic gains of adversaries by more than 99.9% when replaying a real-world trading dataset. A deployment on low-resource devices reveals that the latency added to a trade by XChange is only 493 milliseconds. Finally, our scalability evaluation shows that XChange achieves over 1’000 trades per second and that its throughput, in terms of trades per second, scales linearly with the system load.

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“Big Tech” companies provide digital services used by billions of people. Recent developments, however, have shown that these companies often abuse their unprecedented market dominance for selfish interests. Meanwhile, decentralized applications without central authority are gaining traction. Decentralized applications critically depend on its users working together. Ensuring that users do not consume too many resources without reciprocating is a crucial requirement for the sustainability of such applications. We present ConTrib, a universal mechanism to maintain fairness in decentralized applications by accounting the work performed by peers. In ConTrib, participants maintain a personal ledger with tamper-evident records. A record describes some work performed by a peer and links to other records. Fraud in ConTrib occurs when a peer illegitimately modifies one of the records in its personal ledger. This is detected through the continuous exchange of random records between peers and by verifying the consistency of incoming records against known ones. Our simple fraud detection algorithm is highly scalable, tolerates significant packet loss, and exhibits relatively low fraud detection times. We experimentally show that fraud is detected within seconds and with low bandwidth requirements. To demonstrate the applicability of our work, we deploy ConTrib in the Tribler file-sharing application and successfully address free-riding behaviour. This two-year trial has resulted in over 160 million records, created by more than 94’000 users.

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Non-Fungible Tokens (NFTs) leverage blockchain technology to certify and transfer ownership of digital assets to individuals. NFTs on the Ethereum blockchain have garnered significant attention recently, with a trading volume of over $2 billion in Q1 2021 only. At the same time, established NFT solutions have low flexibility, limited scalability, and high transaction fees. These deficiencies make them impractical to use at a larger scale to manage digital assets. We present UniCon, a universal and scalable infrastructure for digital asset management. The key idea of UniCon is to track asset ownership in a tracking blockchain while making minimal assumptions on the capabilities of this blockchain. UniCon enables the exchange of asset ownership in any digital currency, unlike current NFT platforms. We devise a system architecture and build a prototype of UniCon. We use a scalable distributed ledger that is highly suitable for the tracking of asset ownership. Our prototype enables a decentralized ecosystem to manage and trade assets.

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In a multi-agent system where agents provide quantifiable work for each other on a voluntary basis, reputation mechanisms are incorporated to induce cooperation. Hereby agents assign their peers numerical scores based on their reported transaction histories. In such systems, adversaries can launch an attack by creating fake identities called Sybils, who report counterfeit transactions among one another, with the aim of increasing their own scores in the eyes of others. This paper provides new results about the Sybil-proofness of reputation mechanisms. We revisit the impossibility result of Seuken and Parkes (2011), who show that strongly-beneficial Sybil attacks cannot be prevented on reputation mechanisms satisfying three particular requirements. We prove that, under a more rigorous set of definitions of Sybil attack benefit, this result no longer holds. We characterise properties under which reputation mechanisms are susceptible to strongly-beneficial Sybil attacks. Building on our results, we propose a minimal set of requirements for reputation mechanisms to achieve resistance to such attacks, which are stronger than the results by Cheng and Friedman (2005), who show Sybil-proofness of certain asymmetric reputation mechanisms. @en

Decentralized systems offer alternatives to Big Tech. However, maintaining availability and correctness despite faults and manipulations in decentralized settings is challenging. In this paper, we introduce a collaborative model that is capable of exposing all observable lying, all cheating, and all faults, while only requiring merely unreliable message exchange. Our model is based on conflicting operations on arbitrary data, set reconciliation, and conflict resolution strategies to deal with branches. It is sufficiently general to support applications like Wikipedia, Github, and Datahub in a non-profit, collaborative, and decentralized form. Our protocol guarantees strong convergence despite any Byzantine nodes. We exhibit four conflict resolution strategies that cover the spectrum of possible use cases. A remarkable property of our model is that two honest nodes are guaranteed to converge despite an arbitrary-large number of faulty nodes.

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Existing digital identity management systems fail to deliver the desirable properties of control by the users of their own identity data, credibility of disclosed identity data, and network-level anonymity. The recently proposed Self-Sovereign Identity (SSI) approach promises to give users these properties. However, we argue that without addressing privacy at the network level, SSI systems cannot deliver on this promise. In this paper we present the design and analysis of our solution TCID, created in collaboration with the Dutch government. TCID is a system consisting of a set of components that together satisfy seven functional requirements to guarantee the desirable system properties. We show that the latency incurred by network-level anonymization in TCID is significantly larger than that of identity data disclosure protocols but is still low enough for practical situations. We conclude that current research on SSI is too narrowly focused on these data disclosure protocols.@en

Preventing the abuse of resources is a crucial requirement in shared-resource systems. This concern can be addressed through a centralized gatekeeper, yet it enables manipulation by the gatekeeper itself. We present ConTrib, a decentralized mechanism for tracking resource usage across different shared-resource systems. In ConTrib, participants maintain a personal ledger with tamper-proof records. A record describes a resource consumption or contribution and links to other records. Fraud, maintaining multiple copies of a personal ledger, is detected by users themselves through the continuous exchange of records and by validating their consistency against known ones. We implement ConTrib and run experiments. Our evaluation with up to 1'000 instances reveals that fraud can be detected within 22 seconds and with moderate bandwidth usage. To demonstrate the applicability of our work, we deploy ConTrib in a Tor-like overlay and show how resource abuse by free-riders is effectively deterred. This longitudinal, large-scale trial has resulted in over 137 million records, created by more than 86'000 volunteers.

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