Online voting is convenient and flexible, but amplifies the risks of voter coercion and vote buying. One promising mitigation strategy enables voters to give a coercer fake voting credentials, which silently cast votes that do not count. Current systems along these lines make problematic assumptions about credential issuance, however, such as strong trust in a registrar and/or in voter-controlled hardware, or expecting voters to interact with multiple registrars. Votegral is the first coercion-resistant voting architecture that leverages the physical security of in-person registration to address these credential-issuance challenges, amortizing the convenience costs of in-person registration by reusing credentials across successive elections. Votegral's registration component, TRIP, gives voters a kiosk in a privacy booth with which to print real and fake credentials on paper, eliminating dependence on trusted hardware in credential issuance. The voter learns and can verify in the privacy booth which credential is real, but real and fake credentials thereafter appear indistinguishable to others. Only voters actually under coercion, a hopefully-rare case, need to trust the kiosk. To achieve verifiability, each paper credential encodes an interactive zero-knowledge proof, which is sound in real credentials but unsound in fake credentials. Voters observe the difference in the order of printing steps, but need not understand the technical details. Experimental results with our prototype suggest that Votegral is practical and sufficiently scalable for real-world elections. User-visible latency of credential issuance in TRIP is at most 19.7 seconds even on resource-constrained kiosk hardware, making it suitable for registration at remote locations or on battery power. A companion usability study indicates that TRIP's usability is competitive with other e-voting systems including some lacking coercion resistance, and formal proofs support TRIP's combination of coercion-resistance and verifiability.

Decentralized storage networks offer services with intriguing possibilities to reduce inequalities in an extremely centralized market. Fair distribution of rewards, however, is still a persistent problem in the current generation of decentralized applications using token-based incentives. They are often disproportionally concentrated with small number of early adopters and high-resourced participants. Incentive mechanisms capable of addressing this problem are still poorly understood. This paper aims to help fill this gap by developing our Tit-forToken (Tit4Tok) model. Tit4Tok realizes incentives based on the triad of altruism (selfless behavior), reciprocity (Tit-for-Tat), and monetary rewards compatible with a free market. Tit4Tok analyzes the effects of storage-, and network-parameters fine-tuning to achieve fair distribution of rewards for participants. We present a comprehensive exploration of different factors when incentivized peers share bandwidth in a libp2p-based network, including uneven distributions emerging when gateways provide data to users outside the network. We quantified the Income-Fairness with the Gini coefficient, using multiple model instantiations and diverse approaches for debt cancellation. We propose regular changes to the gateway neighborhood and show that our shuffling method improves the Income-Fairness from 0.66 to 0.16. We quantified the non-negligible cost of tolerating free-riding (altruism). The performance is evaluated by extensive computer simulations and using an IPFS workload to study the effects of caching.

Online voting is attractive for convenience and accessibility, but is more susceptible to voter coercion and vote buying than in-person voting. One mitigation is to give voters fake voting credentials that they can yield to a coercer. Fake credentials appear identical to real ones, but cast votes that are silently omitted from the final tally. An important unanswered question is how ordinary voters perceive such a mitigation: whether they could understand and use fake credentials, and whether the coercion risks justify the costs of mitigation. We present the first systematic study of these questions, involving 150 diverse individuals in Boston, Massachusetts. All participants "registered" and "voted" in a mock election: 120 were exposed to coercion resistance via fake credentials, the rest forming a control group. Of the 120 participants exposed to fake credentials, 96% understood their use. 53% reported that they would create fake credentials in a real-world voting scenario, given the opportunity. 10% mistakenly voted with a fake credential, however. 22% reported either personal experience with or direct knowledge of coercion or vote-buying incidents. These latter participants rated the coercion-resistant system essentially as trustworthy as in-person voting via hand-marked paper ballots. Of the 150 total participants to use the system, 87% successfully created their credentials without assistance; 83% both successfully created and properly used their credentials. Participants give a System Usability Scale score of 70.4, which is slightly above the industry’s average score of 68. Our findings appear to support the importance of the coercion problem in general, and the promise of fake credentials as a possible mitigation, but user error rates remain an important usability challenge for future work.

Front-running attacks, which benefit from advanced knowledge of pending transactions, have proliferated in the blockchain space since the emergence of decentralized finance. Front-running causes devastating losses to honest participants and continues to endanger the fairness of the ecosystem. We present Flash Freezing Flash Boys (F3B), a blockchain architecture that addresses front-running attacks by using threshold cryptography. In F3B, a user generates a symmetric key to encrypt their transaction, and once the underlying consensus layer has finalized the transaction, a decentralized secret-management committee reveals this key. F3B mitigates front-running attacks because, before the consensus group finalizes it, an adversary can no longer read the content of a transaction, thus preventing the adversary from benefiting from advanced knowledge of pending transactions. Unlike other mitigation systems, F3B properly ensures that all unfinalized transactions, even with significant delays, remain private by adopting per-transaction protection. Furthermore, F3B addresses front-running at the execution layer; thus, our solution is agnostic to the underlying consensus algorithm and compatible with existing smart contracts. We evaluated F3B on Ethereum with a modified execution layer and found only a negligible (0.026%) increase in transaction latency, specifically due to running threshold decryption with a 128-member secret-management committee after a transaction is finalized; this indicates that F3B is both practical and low-cost.

Leader-based consensus algorithms are fast and efficient under normal conditions, but lack robustness to adverse conditions due to their reliance on timeouts for liveness. We present QuePaxa, the first protocol offering state-of-the-art normal-case efficiency without depending on timeouts. QuePaxa uses a novel randomized asynchronous consensus core to tolerate adverse conditions such as denial-of-service (DoS) attacks, while a one-round-trip fast path preserves the normal-case efficiency of Multi-Paxos or Raft. By allowing simultaneous proposers without destructive interference, and using short hedging delays instead of conservative timeouts to limit redundant effort, QuePaxa permits rapid recovery after leader failure without risking costly view changes due to false timeouts. By treating leader choice and hedging delay as a multi-armed-bandit optimization, QuePaxa achieves responsiveness to prevalent conditions, and can choose the best leader even if the current one has not failed. Experiments with a prototype confirm that QuePaxa achieves normal-case LAN and WAN performance of 584k and 250k cmd/sec in throughput, respectively, comparable to Multi-Paxos. Under conditions such as DoS attacks, misconfigurations, or slow leaders that severely impact existing protocols, we find that QuePaxa remains live with median latency under 380ms in WAN experiments.

In cryptographic decentralized storage systems, files are split into chunks and distributed across a network of peers. These storage systems encode files using Merkle trees, a hierarchical data structure that provides integrity verification and lookup services. A Merkle tree maps the chunks of a file to a single root whose hash value is the file's content-address.

Data centres that use consumer-grade disks drives and distributed peer-to-peer systems are unreliable environments to archive data without enough redundancy. Most redundancy schemes are not completely effective for providing high availability, durability and integrity in the long-term. We propose alpha entanglement codes, a mechanism that creates a virtual layer of highly interconnected storage devices to propagate redundant information across a large scale storage system. Our motivation is to design flexible and practical erasure codes with high fault-tolerance to improve data durability and availability even in catastrophic scenarios. By "flexible and practical", we mean code settings that can be adapted to future requirements and practical implementations with reasonable trade-offs between security, resource usage and performance. The codes have three parameters. Alpha increases storage overhead linearly but increases the possible paths to recover data exponentially. Two other parameters increase fault-tolerance even further without the need of additional storage. As a result, an entangled storage system can provide high availability, durability and offer additional integrity: it is more difficult to modify data undetectably. We evaluate how several redundancy schemes perform in unreliable environments and show that alpha entanglement codes are flexible and practical codes. Remarkably, they excel at code locality, hence, they reduce repair costs and become less dependent on storage locations with poor availability. Our solution outperforms Reed-Solomon codes in many disaster recovery scenarios.

Two-dimensional square RAID arrays organize their data disks in such a way that each of them belongs to exactly one row parity stripe and one column parity stripe. Even so, they remain vulnerable to the loss of any given data disk and the parity disks of its two stripes. We show how to eliminate all but one of these fatal triple failures by entangling the parity disks of the array, that is, XORing the contents of each parity disk with that of its predecessors. As a result, our new organization reduces the number of fatal triple failures by 96 to 99 percent and the number of fatal quadruple failures by around 85 percent without the need for any additional hardware.

We create a framework to simulate the behavior of different erasure codes. This environment is an ideal research playground for examining entanglement codes. It also provide tools to evaluate and compare entanglement with other codes. Particularly, it allows to run simulations and understand how different code settings provide trade-offs between security and code performance. Choosing the best coding parameters for a storage system is a complex task. When distributing redundant data in a large scale storage system, the number of different locations and the way data is distributed plays an important role in the chances of data to survive failures. This playground let us play with different factors that impact on a storage system. We think it is a useful resource for researchers and engineers working on the design of reliable storage systems.

We study the reliability of open and close entanglements, two simple data distribution layouts for log-structured append-only storage systems. Both techniques use equal numbers of data and parity drives and generate their parity data by computing the exclusive or (XOR) of the most recently appended data with the contents of their last parity drive. While open entanglements maintain an open chain of data and parity drives, closed entanglements include the exclusive or of the contents of their first and last data drives. We evaluate five-year reliabilities of open and closed entanglements, for two different array sizes and drive failure rates. Our results show that open entanglements provide much better five-year reliabilities than mirroring and reduce the probability of a data loss by at least 90 percent over a period of five years. Closed entanglements perform even better and reduce the same probability by at least 98 percent.

Data entanglement is a novel approach to generate and propagate redundancy across multiple disk nodes in a fault-tolerant data store. In this paper, we analyse and evaluate helical entanglement codes (HEC), an XOR-based erasure coding algorithm that constructs long sequences of entangled data using incoming data and stored parities. The robust topology guarantees low complexity and a greater resilience to failures than previous codes mentioned in the literature, however, the code pattern requires a minimum fixed amount of storage overhead. A unique characteristic of HEC is that fault tolerance depends on the number of distinct helical strands (p), a parameter that could be changed on the fly and does not add significantly more storage. A p-HEC setting can tolerate arbitrary 5+p failures. Decoding has a low reconstruction cost and good locality. Besides, a deep repair mechanism exploits the available global parities. We perform experiments to compare the repairability of HEC with other codes and present analytical results of its reliability.