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This document introduces XinFin DPoS 2.0, the proposed next generation decentralized consensus engine for the XinFin XDC Network. Built upon the most advanced BFT consensus protocol, this upgrade will empower the XDC Network with military-grade security and performance while consuming extremely low resources, and will be fully backwards-compatible in terms of APIs. It will also pave the road to the future evolution of the XDC Network. The core invention is the holistic integration of accountability and forensics in blockchains: the ability to identify malicious actors with cryptographic integrity directly from the blockchain records, incorporating the latest peer-reviewed academic research with state of the art engineering designs and implementation plans.
Byzantine fault tolerant (BFT) consensus protocols are traditionally developed to support reliable distributed computing. For applications where the protocol participants are economic agents, recent works highlighted the importance of accountability: the ability to identify participants who provably violate the protocol. We propose to evaluate the security of an accountable protocol in terms of its liveness resilience, the minimum number of Byzantine nodes when liveness is violated, and its accountable safety resilience, the minimum number of accountable Byzantine nodes when safety is violated. We characterize the optimal tradeoffs between these two resiliences in different network environments, and identify an availability-accountability dilemma: in an environment with dynamic participation, no protocol can simultaneously be accountably-safe and live. We provide a resolution to this dilemma by constructing an optimally-resilient accountability gadget to checkpoint a longest chain protocol, such that the full ledger is live under dynamic participation and the checkpointed prefix ledger is accountable. Our accountability gadget construction is black-box and can use any BFT protocol which is accountable under static participation. Using HotStuff as the black box, we implemented our construction as a protocol for the Ethereum 2.0 beacon chain, and our Internet-scale experiments with more than 4000 nodes show that the protocol can achieve the required scalability and has better latency than the current solution Gasper, while having the advantage of being provably secure. To contrast, we demonstrate a new attack on Gasper.
Byzantine fault-tolerant (BFT) protocols allow a group of replicas to come to a consensus even when some of the replicas are Byzantine faulty. There exist multiple BFT protocols to securely tolerate an optimal number of faults $t$ under different network settings. However, if the number of faults $f$ exceeds $t$ then security could be violated. In this paper we mathematically formalize the study of forensic support of BFT protocols: we aim to identify (with cryptographic integrity) as many of the malicious replicas as possible and in as a distributed manner as possible. Our main result is that forensic support of BFT protocols depends heavily on minor implementation details that do not affect the protocols security or complexity. Focusing on popular BFT protocols (PBFT, HotStuff, Algorand) we exactly characterize their forensic support, showing that there exist minor variants of each protocol for which the forensic supports vary widely. We show strong forensic support capability of LibraBFT, the consensus protocol of Diem cryptocurrency; our lightweight forensic module implemented on a Diem client is open-sourced and is under active consideration for deployment in Diem. Finally, we show that all secure BFT protocols designed for $2t+1$ replicas communicating over a synchronous network forensic support are inherently nonexistent; this impossibility result holds for all BFT protocols and even if one has access to the states of all replicas (including Byzantine ones).
Existing permissioned blockchain systems designate a fixed and explicit group of committee nodes to run a consensus protocol that confirms the same sequence of blocks among all nodes. Unfortunately, when such a permissioned blockchain runs in a large scale on the Internet, these explicit committee nodes can be easily turned down by denial-of-service (DoS) or network partition attacks. Although work proposes scalable BFT protocols that run on a larger number of committee nodes, their efficiency drops dramatically when only a small number of nodes are attacked. In this paper, our EGES protocol leverages Intel SGX to develop a new abstraction called stealth committee, which effectively hides the committee nodes into a large pool of fake committee nodes. EGES selects a distinct group of stealth committee for each block and confirms the same sequence of blocks among all nodes with overwhelming probability. Evaluation on typical geo-distributed settings shows that: (1)EGES is the first permissioned blockchains consensus protocol that can tolerate tough DoS and network partition attacks; and (2) EGES achieves comparable throughput and latency as existing permissioned blockchains protocols
We describe and implement a policy language. In our system, agents can distribute data along with usage policies in a decentralized architecture. Our language supports the specification of conditions and obligations, and also the possibility to refine policies. In our framework, the compliance with usage policies is not actively enforced. However, agents are accountable for their actions, and may be audited by an authority requiring justifications.
We provide a UTXO model of blockchain transactions that is able to represent both credit and debt on the same blockchain. Ordinarily, the UTXO model is solely used to represent credit and the representation of credit and debit together is achieved using the account model because of its support for balances. However, the UTXO model provides superior privacy, safety, and scalability when compared to the account model. In this work, we introduce a UTXO model that has the flexibility of balances with the usual benefits of the UTXO model. This model extends the conventional UTXO model, which represents credits as unmatched outputs, by representing debts as unmatched inputs. We apply our model to solving the problem of transparency in reverse mortgage markets, in which some transparency is necessary for a healthy market but complete transparency leads to adverse outcomes. Here the pseudonymous properties of the UTXO model protect the privacy of loan recipients while still allowing an aggregate view of the loan market. We present a prototype of our implementation in Tendermint and discuss the design and its benefits.