搜索结果：Centralization

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 pro

A decentralized autonomous organization (DAO) is a governing entity that empowers its stakeholders (i.e., users who hold one or more of its tokens) to manage blockchain-based protocols (i.e., smart contracts) collaboratively. The governance of a DAO is explicitly encoded in the DAO's governance contract, which defines how stakeholders participate in governance and how much influence (or voting power) they have in any decision. While decentralization and autonomy are the fundamental tenets of a DAO's design, empirical evidence suggests that in practice governance is often highly centralized. In this work, we study the designs and implementations of 48 public and actively used DAOs, with substantially large capital, deployed on Ethereum. We identify how three key governance mechanisms--token registration, staking, and delegation--originally introduced to improve security or participation, contribute to the concentration of voting power. Unlike prior work on centralization of voting power in specific DAOs, our findings reveal that these governance mechanisms of DAOs themselves systematically reinforce centralization. By elucidating the relationship between governance design and voting

In recent years, security incidents stemming from centralization defects in smart contracts have led to substantial financial losses. A centralization defect refers to any error, flaw, or fault in a smart contract's design or development stage that introduces a single point of failure. Such defects allow a specific account or user to disrupt the normal operations of smart contracts, potentially causing malfunctions or even complete project shutdowns. Despite the significance of this issue, most current smart contract analyses overlook centralization defects, focusing primarily on other types of defects. To address this gap, our paper introduces six types of centralization defects in smart contracts by manually analyzing 597 Stack Exchange posts and 117 audit reports. For each defect, we provide a detailed description and code examples to illustrate its characteristics and potential impacts. Additionally, we introduce a tool named CDRipper (Centralization Defects Ripper) designed to identify the defined centralization defects. Specifically, CDRipper constructs a permission dependency graph (PDG) and extracts the permission dependencies of functions from the source code of smart cont

Some smart contracts violate decentralization principles by defining privileged accounts that manage other users' assets without permission, introducing centralization risks that have caused financial losses. Existing methods, however, face challenges in accurately detecting diverse centralization risks due to their dependence on predefined behavior patterns. In this paper, we propose JANUS, an automated analyzer for Solidity smart contracts that detects financial centralization risks independently of their specific behaviors. JANUS identifies differences between states reached by privileged and ordinary accounts, and analyzes whether these differences are finance-related. Focusing on the impact of risks rather than behaviors, JANUS achieves improved accuracy compared to existing tools and can uncover centralization risks with unknown patterns. To evaluate JANUS's performance, we compare it with other tools using a dataset of 540 contracts. Our evaluation demonstrates that JANUS outperforms representative tools in terms of detection accuracy for financial centralization risks . Additionally, we evaluate JANUS on a real-world dataset of 33,151 contracts, successfully identifying two

This study investigates the rapid centralization of the Ethereum builder market under the Proposer-Builder Separation (PBS) architecture. We argue that existing research, by focusing predominantly on influential order flows, lacks a comprehensive evaluation of order flow behavioral patterns and economic purposes. To address this gap, we analyze Ethereum transactions from September 2023 to August 2025 to characterize Exclusive Order Flows (EOFs) and non-atomic Maximal Extractable Value (MEV) -- the missing components corresponding to these behavioral and economic dimensions, respectively. We introduce a novel exclusivity metric based on Kullback-Leibler divergence and employ supervised learning to identify 75 EOFs and 322 non-atomic MEV flows, which account for 71\% and 23\% of trading-related builder revenue. A longitudinal analysis of builder strategies across these dimensions delineates the market's evolution into four distinct eras, revealing that while EOFs were instrumental in establishing early dominance, incumbents have since decoupled market share from immediate EOF dependency by leveraging entrenched network effects. Ultimately, we conclude that builder centralization is a

Over the past decade, Internet centralization and its implications for both people and the resilience of the Internet has become a topic of active debate. While the networking community informally agrees on the definition of centralization, we lack a formal metric for quantifying centralization, which limits research beyond descriptive analysis. In this work, we introduce a statistical measure for Internet centralization, which we use to better understand how the web is centralized across four layers of web infrastructure (hosting providers, DNS infrastructure, TLDs, and certificate authorities) in 150~countries. Our work uncovers significant geographical variation, as well as a complex interplay between centralization and sociopolitically driven regionalization. We hope that our work can serve as the foundation for more nuanced analysis to inform this important debate.

Modern neural network based speech recognition models are required to continually absorb new data without re-training the whole system, especially in downstream applications using foundation models, having no access to the original training data. Continually training the models in a rehearsal-free, multilingual, and language agnostic condition, likely leads to catastrophic forgetting, when a seemingly insignificant disruption to the weights can destructively harm the quality of the models. Inspired by the ability of human brains to learn and consolidate knowledge through the waking-sleeping cycle, we propose a continual learning approach with two distinct phases: factorization and centralization, learning and merging knowledge accordingly. Our experiments on a sequence of varied code-switching datasets showed that the centralization stage can effectively prevent catastrophic forgetting by accumulating the knowledge in multiple scattering low-rank adapters.

In "Faces of a Hyperplane Arrangement Enumerated by Ideal Dimension, with Applications to Plane, Plaids, and Shi," Zaslavsky showed how to compute the number $r_\ell(\mathcal{A})$ of regions of a real hyperplane arrangement $\mathcal{A}$ with a given level, refining his well known enumeration of regions and relatively bounded regions. We restate this theorem in terms of a construction called the centralization of $\mathcal{A}$, give a bijective proof, and then apply it in two ways to answer questions concerning the concept of level. Firstly, a consequence of this enumeration is that $r_\ell(\mathcal{A})$ depends only on the intersection poset $\mathcal{L}(\mathcal{A})$, such that both $r_\ell$ and centralization can be defined in the more general setting of geometric semilattices. In this context we derive a very general expression for the characteristic polynomial of a geometric semilattice with several interesting corollaries. Secondly, recent investigations into the phenomenon of level have made little use of Zaslavsky's level-counting theorem, but it can be applied to obtain or generalize many of their results. In particular we show how exponential generating function identitie

Person re-identification (ReID) aims to extract accurate identity representation features. However, during feature extraction, individual samples are inevitably affected by noise (background, occlusions, and model limitations). Considering that features from the same identity follow a normal distribution around identity centers after training, we propose a Training-Free Feature Centralization ReID framework (Pose2ID) by aggregating the same identity features to reduce individual noise and enhance the stability of identity representation, which preserves the feature's original distribution for following strategies such as re-ranking. Specifically, to obtain samples of the same identity, we introduce two components: Identity-Guided Pedestrian Generation: by leveraging identity features to guide the generation process, we obtain high-quality images with diverse poses, ensuring identity consistency even in complex scenarios such as infrared, and occlusion. Neighbor Feature Centralization: it explores each sample's potential positive samples from its neighborhood. Experiments demonstrate that our generative model exhibits strong generalization capabilities and maintains high identity co

SSL/TLS is a fundamental technology in the network protocol stack that enables encrypted data transmission and authentication of web domains. However, the current model relies on a small number of Certificate Authorities (CAs) to provide and validate certificates, thus creating a highly centralized ecosystem. In this paper, we analyze the degree of centralization of certificate provisioning from CAs in two major political groups: Brazil, Russia, India, China, and South Africa (BRICS) and the European Union (EU). We have found that over 75% of certificates for both BRICS and EU domains originate from CAs based in the United States, indicating possible risks to their digital sovereignty due to the high level of external dependency. This indicates the need for nations within those groups to research alternatives to reduce the high level of dependency on foreign CAs and increase their digital autonomy.

The goal of this paper is to rigorously interrogate conventional wisdom about centralization in block-building (due to, e.g., MEV and private order flow) and the outsourcing of block-building by validators to specialists (i.e., proposer-builder separation): 1. Does heterogeneity in skills and knowledge across block producers inevitably lead to centralization? 2. Does proposer-builder separation eliminate heterogeneity and preserve decentralization among proposers? This paper develops mathematical models and results that offer answers to these questions: 1. In a game-theoretic model with endogenous staking, heterogeneous block producer rewards, and staking costs, we quantify the extent to which heterogeneous rewards lead to concentration in the equilibrium staking distribution. 2. In a stochastic model in which heterogeneous block producers repeatedly reinvest rewards into staking, we quantify, as a function of the block producer heterogeneity, the rate at which stake concentrates on the most sophisticated block producers. 3. In a model with heterogeneous proposers and specialized builders, we quantify, as a function of the competitiveness of the builder ecosystem, the extent to whi

Smart contract access control mechanisms can introduce centralization into supposedly decentralized ecosystems. In our view, such centralization is an overlooked risk of smart contracts that underlies well-known smart contract security incidents. Critically, mitigating the known vulnerability of missing permission verification by implementing authorization patterns can in turn introduce centralization. To delineate the issue, we define centralization risk and describe smart contract source code patterns for Ethereum and Algorand that can introduce it to smart contracts. We explain under which circumstances the centralization can be exploited. Finally, we discuss implications of centralization risk for different smart contract stakeholders.

Current automotive E/E architectures are subject to significant transformations: Computing-power-intensive advanced driver-assistance systems, bandwidth-hungry infotainment systems, the connection of the vehicle with the internet and the consequential need for cyber-security drives the centralization of E/E architectures. A centralized architecture is often seen as a key enabler to master those challenges. Available research focuses mostly on the different types of E/E architectures and contrasts their advantages and disadvantages. There is a research gap on guidelines for system designers and function developers to analyze the potential of their systems for centralization. The present paper aims to quantify centralization potential reviewing relevant literature and conducting qualitative interviews with industry practitioners. In literature, we identified seven key automotive system properties reaching limitations in current automotive architectures: busload, functional safety, computing power, feature dependencies, development and maintenance costs, error rate, modularity and flexibility. These properties serve as quantitative evaluation criteria to estimate whether centralizatio

In swarm robotics, decentralized control is often proposed as a more scalable and fault-tolerant alternative to centralized control. However, centralized behaviors are often faster and more efficient than their decentralized counterparts. In any given application, the goals and constraints of the task being solved should guide the choice to use centralized control, decentralized control, or a combination of the two. Currently, the exact trade-offs that exist between centralization and decentralization are not well defined. In this paper, we compare the performance of centralization and decentralization in the example task of sweep coverage, across five different types of multi-robot control structures: random walk, decentralized with beacons, hybrid formation control using self-organizing hierarchy, centralized formation control, and predetermined. In all five approaches, the coverage task is completed by a group of ground robots. In each approach, except for the random walk, the ground robots are assisted by UAVs, acting as supervisors or beacons. We compare the approaches in terms of three performance metrics for which centralized approaches are expected to have an advantage -- c

This paper aims to provide a new perspective on the interplay between decentralization -- a prevalent character of multi-agent systems -- and centralization, i.e., the task of imposing central control to meet system-level goals. In particular, in the context of networked opinion dynamic model, the paper proposes and discusses a framework for centralization. More precisely, a decentralized network consists of autonomous agents and their social structure that is unknown and dynamic. Centralization is a process of appointing agents in the network to act as access units who provide information and exert influence over their local surroundings. We discuss centralization for the DeGroot model of opinion dynamics, aiming to enforce opinion convergence using the minimum number of access units. We show that the key to the centralization process lies in selecting access units so that they form a dominating set. We then propose algorithms under a new local algorithmic framework, namely prowling, to accomplish this task. To validate our algorithm, we perform systematic experiments over both real-world and synthetic networks and verify that our algorithm outperforms benchmarks.

One of the most important features of blockchain protocols is decentralization, as their main contribution is that they formulate a distributed ledger that will be maintained and extended without the need of a trusted party. Bitcoin has been criticized for its tendency to centralization, as very few pools control the majority of the hashing power. Pass et al. proposed FruitChain [PODC 17] and claimed that this blockchain protocol mitigates the formation of pools by reducing the variance of the rewards in the same way as mining pools, but in a fully decentralized fashion. Many follow up papers consider that the problem of centralization in Proof-of-Work (PoW) blockchain systems can be solved via lower rewards' variance, and that in FruitChain the formation of pools is unnecessary. Contrary to the common perception, in this work, we prove that lower variance of the rewards does not eliminate the tendency of the PoW blockchain protocols to centralization; miners have also other incentives to create large pools, and specifically to share the cost of creating the instance they need to solve the PoW puzzle. We abstract the procedures of FruitChain as oracles and assign to each of them a

Consider a social-choice function (SCF) is chosen to decide votes in a formal system, including votes to replace the voting method itself. Agents vote according to their ex-ante belief over what decisions are considered, and whether they prefer them to be decided by the incumbent SCF or the suggested replacement. The existing SCF then aggregates the agents' votes and arrives at a decision of whether it should itself be replaced. An SCF is self-maintaining if it can not be replaced in such fashion by any other SCF. Our focus is on the implications of self-maintenance for centralization. For this purpose, unlike [Barbera and Jackson, 2004], we do not generally restrict attention to anonymous SCFs. We also do not restrict attention to neutral SCFs, unlike [Koray, 2000]. We present results considering optimistic, pessimistic and i.i.d. approaches with respect to agent beliefs, different tie-breaking rules, and different SCF domains. To highlight two of the results, (i) for the i.i.d. unbiased case with arbitrary tie-breaking and general Boolean functions, we prove an Arrow-Style Theorem for Dynamics: We show that only a dictatorship is self-maintaining, and any other SCF has a path of

We introduce the extended centralized circumcentered reflection method (ecCRM), a framework for two-set convex feasibility that encompasses the classical centralized CRM (cCRM) of Behling, Bello-Cruz, Iusem and Santos as a special case. Our method replaces the fixed centralization step of cCRM with an admissible operator $T$ and a parameter $α$, allowing control over computational cost and step quality. We show that ecCRM retains global convergence, linear rates under mild regularity, and superlinearity for smooth manifolds. Numerical experiments on large-scale matrix completion indicate that deeper operators can dramatically reduce overall runtime, and tests on high-dimensional ellipsoids show that vanishing step sizes can yield significant acceleration, validating the practical utility of both algorithmic components of ecCRM.