Kendric Hood, Joseph Oglio, Mikhail Nesterenko, Gokarna Sharma
We consider operation of blockchain-based cryptocurrency in case of partitioning. We define the Partitionable Blockchain Consensus Problem. The problem may have an interesting solution if the partitions proceed independently by splitting accounts. We prove that this problem is not solvable in the asynchronous system. The peers in the two partitions may not agree on the last jointly mined block or, alternatively, on the starting point of independent concurrent computation. We introduce a family of detectors that enable a solution. We establish the relationship between detectors. We present the algorithm that solves the Partitionable Blockchain Consensus Problem using our detectors. We extend our solution to multiple splits, message loss and to partition merging. We simulate and evaluate the performance of detectors, discuss the implementation of the detectors and future work.
Payment channels networks drastically increase the throughput and hence scalability of blockchains by performing transactions \emph{off-chain}. In an off-chain payment, parties deposit coins in a channel and then perform transactions without invoking the global consensus mechanism of the blockchain. However, the transaction value is limited by the capacity of the channel, i.e., the amount of funds available on a channel. These funds decrease when a transaction is sent and increase when a transaction is received on the channel. Recent research indicates that there is an imbalance between sending and receiving transactions, which leads to channel depletion in the sense that one of these operations becomes impossible over time due to the lack of available funds. We incentivize the balanced use of payment channels through fees. Whereas the current fee model depends solely on the transaction value, our fee policies encourage transactions that have a positive effect on the balance in a channel and discourage those that have a negative effect. This paper first defines necessary properties of fee strategies. Then, it introduces two novel fees strategies that provably satisfy all necessary properties. Our extensive simulation study reveals that these incentives increase the effectiveness of payments by $8\%$ to $19\%$.
Emmanuelle Anceaume, Antonella Pozzo, Thibault Rieutord, Sara Tucci-Piergiovanni
There exist many forms of Blockchain finality conditions, from deterministic to probabilistic terminations. To favor availability against consistency in the face of partitions, most blockchains only offer probabilistic eventual finality: blocks may be revoked after being appended to the blockchain, yet with decreasing probability as they sink deeper into the chain. Other blockchains favor consistency by leveraging the immediate finality of Consensus-a block appended is never revoked-at the cost of additional synchronization. In this paper, we focus on necessary and sufficient conditions to implement a blockchain with deterministic eventual finality, which ensures that selected main chains at different processes share a common increasing prefix. This is a much weaker form of finality that allows us to provide a solution in an asynchronous system subject to unlimited number of byzantine failures. We study stronger forms of eventual finality as well and show that it is unfortunately impossible to provide a bounded displacement. By bounded displacement we mean that the (unknown) number of blocks that can be revoked from the current blockchain is bounded. This problem reduces to consensus or eventual consensus depending on whether the bound is known or not. We also show that the classical selection mechanism, such as in Bitcoin, that appends blocks at the longest chain is not compliant with a solution to eventual finality.
We have entered an era where the importance of decentralized solutions has become more obvious. Blockchain technology and its derivatives are distributed ledger technologies that keep the registry of data between peers of a network. This ledger is secured within a successive over looping cryptographic chain. The accomplishment of the Bitcoin cryptocurrency proved that blockchain technology and its derivatives could be used to eliminate intermediaries and provide security for cyberspace. However, there are some challenges in the implementation of blockchain technology. This chapter first explains the concept of blockchain technology and the data that we can store therein. The main advantage of blockchain is the security services that it provides. This section continues by describing these services.. The challenges of blockchain; blockchain anomalies, energy consumption, speed, scalability, interoperability, privacy and cryptology in the age of quantum computing are described. Selected solutions for these challenges are given. Remarkable derivatives of blockchain, which use different solutions (directed acyclic graph, distributed hash table, gossip consensus protocol) to solve some of these challenges are described. Then the data storage in blockchain and evolving data solutions are explained. The comparison of decentralized solutions with the lcentralized database systems is given. A multi-platform interoperable scalable architecture (MPISA) is proposed. In the conclusion we include the evolution assumptions of data storage in a decentralized world.
Blockchain plays an important role in cryptocurrency markets and technology services. However, limitations on high latency and low scalability retard their adoptions and applications in classic designs. Reconstructed blockchain systems have been proposed to avoid the consumption of competitive transactions caused by linear sequenced blocks. These systems, instead, structure transactions/blocks in the form of Directed Acyclic Graph (DAG) and consequently re-build upper layer components including consensus, incentives, \textit{etc.} The promise of DAG-based blockchain systems is to enable fast confirmation (complete transactions within million seconds) and high scalability (attach transactions in parallel) without significantly compromising security. However, this field still lacks systematic work that summarises the DAG technique. To bridge the gap, this Systematization of Knowledge (SoK) provides a comprehensive analysis of DAG-based blockchain systems. Through deconstructing open-sourced systems and reviewing academic researches, we conclude the main components and featured properties of systems, and provide the approach to establish a DAG. With this in hand, we analyze the security and performance of several leading systems, followed by discussions and comparisons with concurrent (scaling blockchain) techniques. We further identify open challenges to highlight the potentiality of DAG-based solutions and indicate their promising directions for future research.
Decentralized management and coordination of energy systems are emerging trends facilitated by the uptake of the Internet of Things and Blockchain offering new opportunities for more secure, resilient, and efficient energy distribution. Even though the use of distributed ledger technology in the energy domain is promising, the development of decentralized smart grid management solutions is in the early stages. In this paper, we define a layered architecture of a blockchain-based smart grid management platform featuring energy data metering and tamper-proof registration, business enforcement via smart contracts, and Oracle-based integration of high computational services supporting the implementation of future grid management scenarios. Three such scenarios are discussed from the perspective of their implementation using the proposed blockchain platform and associated challenges: peer to peer energy trading, decentralized management, and aggregation of energy flexibility and operation of community oriented Virtual Power Plants.
Services computing can offer a high-level abstraction to support diverse applications via encapsulating various computing infrastructures. Though services computing has greatly boosted the productivity of developers, it is faced with three main challenges: privacy and security risks, information silo, and pricing mechanisms and incentives. The recent advances of blockchain bring opportunities to address the challenges of services computing due to its build-in encryption as well as digital signature schemes, decentralization feature, and intrinsic incentive mechanisms. In this paper, we present a survey to investigate the integration of blockchain with services computing. The integration of blockchain with services computing mainly exhibits merits in two aspects: i) blockchain can potentially address key challenges of services computing and ii) services computing can also promote blockchain development. In particular, we categorize the current literature of services computing based on blockchain into five types: services creation, services discovery, services recommendation, services composition, and services arbitration. Moreover, we generalize Blockchain as a Service (BaaS) architecture and summarize the representative BaaS platforms. In addition, we also outline open issues of blockchain-based services computing and BaaS.
We present Egalitarian BFT (EBFT), a simple and high-performance framework of BFT consensus protocols for decentralized systems like blockchains. The key innovation in EBFT is egalitarian block generation: nodes randomly and non-interactively propose blocks containing client transactions, rather than relying on a leader to do so. Apart from deterministic safety and liveness guarantees standard in BFT protocols, the egalitarian design provides two novel features: (i) EBFT is resilient to attacks targeting the leader, such as bribery and targeted DoS attacks, and (ii) EBFT does not require any fail-over protocol to detect and replace the faulty leader. EBFT consists of three protocols: EBFT-Syn for synchronous networks, EBFT-PSyn for partially synchronous networks, and EBFT-Turbo that builds on EBFT for high performance. We implement EBFT and evaluate its performance on AWS. To compare EBFT with state-of-the-art BFT protocols, we build EBFT-PSyn based on Bamboo, an open-source platform for prototyping partially synchronous BFT protocols. We evaluate EBFT-PSyn and HotStuff on EC2 with up to 16 nodes. The evaluation shows that EBFT-PSyn achieves better throughput and latency than HotStuff. To demonstrate its simplicity and practicality, we build EBFT on the Go version of Bitcoin, btcd. We implemented EBFT-Syn, EBFT-PSyn and EBFT-Turbo in about 920 LoCs in total. This indicates that EBFT can be built on top of existing blockchains with relatively little effort. We evaluate these protocols on EC2 instances with up to 256 nodes. Our evaluation shows that EBFT-Syn (resp. EBFT-PSyn) achieves a latency of 6 (resp. 1) seconds, and an optimized version of EBFT-PSyn processes up to 3.6k transactions per second and has a latency of 8 seconds.
EIP-1559 is a proposal to make several tightly coupled additions to Ethereum's transaction fee mechanism, including variable-size blocks and a burned base fee that rises and falls with demand. This report assesses the game-theoretic strengths and weaknesses of the proposal and explores some alternative designs.
Ignacio Amores-Sesar, Christian Cachin, Jovana Mićić
The Ripple network is one of the most prominent blockchain platforms and its native XRP token currently has one of the highest cryptocurrency market capitalizations. The Ripple consensus protocol powers this network and is generally considered to a Byzantine fault-tolerant agreement protocol, which can reach consensus in the presence of faulty or malicious nodes. In contrast to traditional Byzantine agreement protocols, there is no global knowledge of all participating nodes in Ripple consensus; instead, each node declares a list of other nodes that it trusts and from which it considers votes. Previous work has brought up concerns about the liveness and safety of the consensus protocol under the general assumptions stated initially by Ripple, and there is currently no appropriate understanding of its workings and its properties in the literature. This paper closes this gap and makes two contributions. It first provides a detailed, abstract description of the protocol, which has been derived from the source code. Second, the paper points out that the abstract protocol may violate safety and liveness in several simple executions under relatively benign network assumptions.
Igor Konnov, Marijana Lazić, Ilina Stoilkovska, Josef Widder
Threshold guards are a basic primitive of many fault-tolerant algorithms that solve classical problems in distributed computing, such as reliable broadcast, two-phase commit, and consensus. Moreover, threshold guards can be found in recent blockchain algorithms such as, e.g., Tendermint consensus. In this article, we give an overview of techniques for automated verification of threshold-guarded fault-tolerant distributed algorithms, implemented in the Byzantine Model Checker (ByMC). These threshold-guarded algorithms have the following features: (1) up to $t$ of processes may crash or behave Byzantine; (2) the correct processes count messages and make progress when they receive sufficiently many messages, e.g., at least $t+1$; (3) the number $n$ of processes in the system is a parameter, as well as the number $t$ of faults; and (4) the parameters are restricted by a resilience condition, e.g., $n > 3t$. Traditionally, these algorithms were implemented in distributed systems with up to ten participating processes. Nowadays, they are implemented in distributed systems that involve hundreds or thousands of processes. To make sure that these algorithms are still correct for that scale, it is imperative to verify them for all possible values of the parameters.
Mirko Zichichi, Stefano Ferretti, Gabriele D’Angelo, Victor Rodrı́guez-Doncel
This paper presents an architecture of a Personal Information Management System, in which individuals can define the access to their personal data by means of smart contracts. These smart contracts, running on the Ethereum blockchain, implement access control lists and grant immutability, traceability and verifiability of the references to personal data, which is stored itself in a (possibly distributed) file system. A distributed authorization mechanism is devised, where trust from multiple network nodes is necessary to grant the access to the data. To this aim, two possible alternatives are described: a Secret Sharing scheme and Threshold Proxy Re-Encryption scheme. The performance of these alternatives is experimentally compared in terms of execution time. Threshold Proxy Re- Encryption appears to be faster in different scenarios, in particular when increasing message size, number of nodes and the threshold value, i.e. number of nodes needed to grant the data disclosure.
Vladimir Yussupov, Ghareeb Falazi, Uwe Breitenbücher, Frank Leymann
Although historically the term serverless was also used in the context of peer-to-peer systems, it is more frequently associated with the architectural style for developing cloud-native applications. From the developer's perspective, serverless architectures allow reducing management efforts since applications are composed using provider-managed components, e.g., Database-as-a-Service (DBaaS) and Function-as-a-Service (FaaS) offerings. Blockchains are distributed systems designed to enable collaborative scenarios involving multiple untrusted parties. It seems that the decentralized peer-to-peer nature of blockchains makes it interesting to consider them in serverless architectures, since resource allocation and management tasks are not required to be performed by users. Moreover, considering their useful properties of ensuring transaction's immutability and facilitating accountable interactions, blockchains might enhance the overall guarantees and capabilities of serverless architectures. Therefore, in this work, we analyze how the blockchain technology and smart contracts fit into the serverless picture and derive a set of scenarios in which they act as different component types in serverless architectures. Furthermore, we formulate the implementation requirements that have to be fulfilled to successfully use blockchains and smart contracts in these scenarios. Finally, we investigate which existing technologies enable these scenarios, and analyze their readiness and suitability to fulfill the formulated requirements.
Most state machine replication protocols are either based on the 40-years-old Byzantine Fault Tolerance (BFT) theory or the more recent Nakamoto's longest chain design. Longest chain protocols, designed originally in the Proof-of-Work (PoW) setting, are available under dynamic participation, but has probabilistic confirmation with long latency dependent on the security parameter. BFT protocols, designed for the permissioned setting, has fast deterministic confirmation, but assume a fixed number of nodes always online. We present a new construction which combines a longest chain protocol and a BFT protocol to get the best of both worlds. Using this construction, we design TaiJi, the first dynamically available PoW protocol which has almost deterministic confirmation with latency independent of the security parameter. In contrast to previous hybrid approaches which use a single longest chain to sample participants to run a BFT protocol, our native PoW construction uses many independent longest chains to sample propose actions and vote actions for the BFT protocol. This design enables TaiJi to inherit the full dynamic availability of Bitcoin, as well as its full unpredictability, making it secure against fully-adaptive adversaries with up to 50% of online hash power.
Data privacy and sharing has always been a critical issue when trying to build complex deep learning-based systems to model data. Facilitation of a decentralized approach that could take benefit from data across multiple nodes while not needing to merge their data contents physically has been an area of active research. In this paper, we present a solution to benefit from a distributed data setup in the case of training deep learning architectures by making use of a smart contract system. Specifically, we propose a mechanism that aggregates together the intermediate representations obtained from local ANN models over a blockchain. Training of local models takes place on their respective data. The intermediate representations derived from them, when combined and trained together on the host node, helps to get a more accurate system. While federated learning primarily deals with the same features of data where the number of samples being distributed on multiple nodes, here we are dealing with the same number of samples but with their features being distributed on multiple nodes. We consider the task of bank loan prediction wherein the personal details of an individual and their bank-specific details may not be available at the same place. Our aggregation mechanism helps to train a model on such existing distributed data without having to share and concatenate together the actual data values. The obtained performance, which is better than that of individual nodes, and is at par with that of a centralized data setup makes a strong case for extending our technique across other architectures and tasks. The solution finds its application in organizations that want to train deep learning models on vertically partitioned data.
Faheem Zafar, Abid Khan, Saif Ur Rehman Malik, Adeel Anjum · 5 authors
Smart devices have accentuated the importance of geolocation information. Geolocation identification using smart devices has paved the path for incentive-based location-based services (LBS). A location proof is a digital certificate of the geographical location of a user, which can be used to access various LBS. However, a user full control over a device allows the tampering of location proof. Initially, to resist false proofs, two-party trusted centralized location proof systems (LPS) were introduced to aid the users in generating secure location proofs mutually. However, two-party protocols suffered from the collusion attacks by the participants of the protocol. Consequently, many witness-oriented LPS have emerged to mitigate collusion attacks in two-party protocols. However, witness-oriented LPS presented the possibility of three-way collusion attacks (involving the user, location authority, and the witness). The three-way collusion attacks are inevitable in all existing witness-oriented schemes. To mitigate the inability to resist three-way collusion of existing schemes, in this paper, we introduce a decentralized consensus protocol called as MobChain, where the selection of a witness and location authority is achieved through a distributed consensus of nodes in an underlying P2P network of a private blockchain. The persistent provenance data over the blockchain provides strong security guarantees, as a result, the forging and manipulation become impractical. MobChain provides secure location provenance architecture, relying on decentralized decision making for the selection of participants of the protocol to resist three-way collusion problem. Our prototype implementation and comparison with the state-of-the-art solutions show that MobChain is computationally efficient, highly available while improving the security of LPS.
Isaac Sheff, Xinwen Wang, Robbert van Renesse, Andrew C. Myers
In distributed systems, a group of $\textit{learners}$ achieve $\textit{consensus}$ when, by observing the output of some $\textit{acceptors}$, they all arrive at the same value. Consensus is crucial for ordering transactions in failure-tolerant systems. Traditional consensus algorithms are homogeneous in three ways: - all learners are treated equally, - all acceptors are treated equally, and - all failures are treated equally. These assumptions, however, are unsuitable for cross-domain applications, including blockchains, where not all acceptors are equally trustworthy, and not all learners have the same assumptions and priorities. We present the first consensus algorithm to be heterogeneous in all three respects. Learners set their own mixed failure tolerances over differently trusted sets of acceptors. We express these assumptions in a novel $\textit{Learner Graph}$, and demonstrate sufficient conditions for consensus. We present $\textit{Heterogeneous Paxos}$: an extension of Byzantine Paxos. Heterogeneous Paxos achieves consensus for any viable Learner Graph in best-case three message sends, which is optimal. We present a proof-of-concept implementation, and demonstrate how tailoring for heterogeneous scenarios can save resources and latency.
This paper presents an autonomous driving that achieves physical layer security. Proposed vehicle communication is implemented based on Proof-of-Nonce (PoN) blockchain algorithm. PoN blockchain algorithm is a consensus algorithm that can be implemented in light weight. We propose a more secure vehicle communication scheme while achieving physical layer security by defecting PoN algorithm and secrecy capacity. By generating a block only when secrecy capacity is greater than or equal to the reference value, traffic information can be provided only to vehicles with physical layer security. This vehicle communication scheme can secure sufficient safety even from hackers based on quantum computing.
Harry Cai, Daniel Rueckert, Jonathan Passerat-Palmbach
Federated Learning harnesses data from multiple sources to build a single model. While the initial model might belong solely to the actor bringing it to the network for training, determining the ownership of the trained model resulting from Federated Learning remains an open question. In this paper we explore how Blockchains (in particular Ethereum) can be used to determine the evolving ownership of a model trained with Federated Learning. Firstly, we use the step-by-step evaluation metric to assess the relative contributivities of participants in a Federated Learning process. Next, we introduce 2CP, a framework comprising two novel protocols for Blockchained Federated Learning, which both reward contributors with shares in the final model based on their relative contributivity. The Crowdsource Protocol allows an actor to bring a model forward for training, and use their own data to evaluate the contributions made to it. Potential trainers are guaranteed a fair share of the resulting model, even in a trustless setting. The Consortium Protocol gives trainers the same guarantee even when no party owns the initial model and no evaluator is available. We conduct experiments with the MNIST dataset that reveal sound contributivity scores resulting from both Protocols by rewarding larger datasets with greater shares in the model. Our experiments also showed the necessity to pair 2CP with a robust model aggregation mechanism to discard low quality inputs coming from model poisoning attacks.
Divija Swetha Gadiraju, V. Lalitha, Vaneet Aggarwal
Blockchain is a distributed ledger with wide applications. Due to the increasing storage requirement for blockchains, the computation can be afforded by only a few miners. Sharding has been proposed to scale blockchains so that storage and transaction efficiency of the blockchain improves at the cost of security guarantee. This paper aims to consider a new protocol, Secure-Repair-Blockchain (SRB), which aims to decrease the storage cost at the miners. In addition, SRB also decreases the bootstrapping cost, which allows for new miners to easily join a sharded blockchain. In order to reduce storage, coding-theoretic techniques are used in SRB. In order to decrease the amount of data that is transferred to the new node joining a shard, the concept of exact repair secure regenerating codes is used. The proposed blockchain protocol achieves lower storage than those that do not use coding, and achieves lower bootstrapping cost as compared to the different baselines.
With the prevalence of Internet of Things (IoT) applications, IoT devices interact closely with our surrounding environments, bringing us unparalleled smartness and convenience. However, the development of secure IoT solutions is getting a long way lagged behind, making us exposed to common unauthorized accesses that may bring malicious attacks and unprecedented danger to our daily life. Overprivilege attack, a widely reported phenomenon in IoT that accesses unauthorized or excessive resources, is notoriously hard to prevent, trace and mitigate. To tackle this challenge, we propose Tokoin-Based Access Control (TBAC), an accountable access control model enabled by blockchain and Trusted Execution Environment (TEE) technologies, to offer fine-graininess, strong auditability, and access procedure control for IoT. TBAC materializes the virtual access power into a definite-amount and secure cryptographic coin termed "tokoin" (token+coin), and manages it using atomic and accountable state-transition functions in a blockchain. We also realize access procedure control by mandating every tokoin a fine-grained access policy defining who is allowed to do what at when in where by how. The tokoin is peer-to-peer transferable, and can be modified only by the resource owner when necessary. We fully implement TBAC with well-studied cryptographic primitives and blockchain platforms and present a readily available APP for regular users. We also present a case study to demonstrate how TBAC is employed to enable autonomous in-home cargo delivery while guaranteeing the access policy compliance and home owner's physical security by regulating the physical behaviors of the deliveryman.
Lower bounds and impossibility results in distributed computing are both intellectually challenging and practically important. Hundreds if not thousands of proofs appear in the literature, but surprisingly, the vast majority of them apply to deterministic algorithms only. Probabilistic protocols have been around for at least four decades and are receiving a lot of attention with the emergence of blockchain systems. Nonetheless, we are aware of only a handful of randomized lower bounds. In this paper we provide a formal framework for reasoning about randomized distributed algorithms. We generalize the notion of indistinguishability, the most useful tool in deterministic lower bounds, to apply to a probabilistic setting. We apply this framework to prove a result of independent interest. Namely, we completely characterize the quality of decisions that protocols for a randomized multi-valued Consensus problem can guarantee in an asynchronous environment with Byzantine faults. We use the new notion to prove a lower bound on the probability at which it can be guaranteed that honest parties will not decide on a possibly bogus value. Finally, we show that the bound is tight by providing a protocol that matches it.
Johannes Sedlmeir, Hans Ulrich Buhl, Gilbert Fridgen, Robert Keller
Zusammenfassung Der enorme Stromverbrauch von Bitcoin hat dazu geführt, dass in Wissenschaft und Praxis oft eher undifferenziert Diskussionen über die Nachhaltigkeit von Blockchain- bzw. Distributed-Ledger-Technologie allgemein geführt werden. Allerdings ist die Blockchain-Technologie bereits heute alles andere als homogen – nicht nur hinsichtlich ihrer Anwendungen, die mittlerweile weit über Kryptowährungen hinaus in Wirtschaft und öffentlichen Sektor reichen, sondern auch bezüglich ihrer technischen Charakteristika und insbesondere ihres Stromverbrauchs. Dieser Beitrag fasst den Status quo des Stromverbrauchs verschiedener Implementierungen von Blockchain-Technologie zusammen und geht dabei besonders auf das kürzlich erfolgte Bitcoin Halving sowie sogenannte ZK-Rollups ein. Wir argumentieren, dass Bitcoin und andere Proof-of-Work-Blockchains zwar in der Tat sehr viel Strom verbrauchen, aber bereits heute alternative Blockchain-Lösungen mit deutlich geringerem Stromverbrauch verfügbar sind und weitere vielversprechende Konzepte erprobt werden, die gerade den Stromverbrauch von großen Blockchain-Netzwerken in naher Zukunft noch einmal deutlich senken könnten. Daraus schließen wir, dass die Kritik am Stromverbrauch von Bitcoin zwar legitim ist, jedoch daraus nicht eine Energieproblematik von Blockchain-Technologie generell abgeleitet werden darf. In vielen Fällen, in denen mithilfe von energieeffizienteren Blockchain-Varianten Prozesse digitalisiert oder verbessert werden können, darf sogar per Saldo durchaus mit Energieeinsparungen gerechnet werden.
Digital identity seems like a prerequisite for digital democracy: how can we ensure "one person, one vote" online without identifying voters? But digital identity solutions - ID checking, biometrics, self-sovereign identity, and trust networks - all present flaws, leaving users vulnerable to exclusion, identity loss or theft, and coercion. These flaws may be insurmountable because digital identity is a cart pulling the horse. We cannot achieve digital identity secure enough for the weight of digital democracy, until we build it on a solid foundation of "digital personhood." While identity is about distinguishing one person from another through attributes or affiliations, personhood is about giving all real people inalienable digital participation rights independent of identity, including protection against erosion of their democratic rights through identity loss, theft, coercion, or fakery. We explore and analyze alternative approaches to "proof of personhood" that may provide this missing foundation. Pseudonym parties marry the transparency of periodic physical-world events with the power of digital tokens between events. These tokens represent limited-term but renewable claims usable for purposes such as online voting or liquid democracy, sampled juries or deliberative polls, abuse-resistant social communication, or minting universal basic income in a permissionless cryptocurrency. Enhancing pseudonym parties to provide participants a moment of enforced physical security and privacy can address coercion and vote-buying risks that plague today's E-voting systems. We also examine other proposed approaches to proof of personhood, some of which offer conveniences such as all-online participation. These alternatives currently fall short of satisfying all the key digital personhood goals, unfortunately, but offer valuable insights into the challenges we face.