12 research outputs found
General Congestion Attack on HTLC-Based Payment Channel Networks
Payment Channel Networks (PCNs) have been a promising approach to scale blockchains. However, PCNs have limited liquidity: large-amount or multi-hop payments may fail. The major threat of PCNs liquidity is payment griefing, where the adversary who acts as the payee keeps withholding the payment, so that coins involved in the payment cannot be used for routing other payments before the payment expires. Payment griefing gives adversaries a chance to launch the congestion attack, where the adversary griefs a large number of payments and paralyses the entire PCN. Understanding congestion attacks, including their strategies and impact, is crucial for designing PCNs with better liquidity guarantees. However, existing research has only focused on the specific attacking strategies and specific aspects of their impact on PCNs.
We fill this gap by studying the general congestion attack. Compared to existing attack strategies, in our framework each step serves an orthogonal purpose and is customisable, allowing the adversary to focus on different aspects of the liquidity. To evaluate the attack\u27s impact, we propose a generic method of quantifying PCNs\u27 liquidity and effectiveness of the congestion attacks. We evaluate our general congestion attacks on Bitcoin\u27s Lightning Network, and show that with direct channels to 1.5% richest nodes, and 0.0096 BTC of cost, the adversary can launch a congestion attack that locks 47% (280 BTC) coins in the network; reduces success rate of payments by 16.0%60.0%; increases fee of payments by 4.5%16.0%; increases average attempts of payments by 42.0%115.3%; and increase the number of bankruptcy nodes (i.e., nodes with insufficient balance for making normal-size payments) by 26.6%109.4%, where the amounts of payments range from 0.001 to 0.019 BTC
On the optionality and fairness of Atomic Swaps
Atomic Swap enables two parties to atomically exchange their own cryptocurrencies without trusted third parties. This paper provides the first quantitative analysis on the fairness of the Atomic Swap protocol, and proposes the first fair Atomic Swap protocol with implementations.
In particular, we model the Atomic Swap as the American Call Option, and prove that an Atomic Swap is equivalent to an American Call Option without the premium. Thus, the Atomic Swap is unfair to the swap participant. Then, we quantify the fairness of the Atomic Swap and compare it with that of conventional financial assets (stocks and fiat currencies). The quantification results show that the the Atomic Swap is much more unfair on cryptocurrencies than on stocks and fiat currencies in the same setting. Moreover, we use the conventional Cox-Ross-Rubinstein option pricing model in Finance to estimate the premium, and show that the estimated premium for cryptocurrencies is 2% ∼ 3% of the asset value, while the premium for stocks and fiat currencies is approximately 0.3%. Furthermore, we propose two fair Atomic Swap protocols, one is for currency exchange and the other is for American Call Options. Our protocols are based on the original Atomic Swap protocol, but implement the premium mechanism. Blockchains supporting smart contracts such as Ethereum support our protocols directly. Blockchains only supporting scripts such as Bitcoin can support our protocols by adding a simple opcode. Finally, we provide the reference implementation of our protocols in Solidity, and give detailed instructions on implementing our protocols with Bitcoin script
Fair Delivery of Decentralised Randomness Beacon
Thesecurityofmanyprotocolssuchasvotingandblockchains relies on a secure source of randomness. Decentralised Randomness Beacon (DRB) has been considered as a promising approach, where a set of participants jointly generates a sequence of random outputs. While the DRBs have been extensively studied, they failed to capture the advantage that some participants learn random outputs earlier than other participants. In time-sensitive protocols whose execution depends on the randomness from a DRB, such an advantage allows the adversary to behave adaptively according to random outputs, compromising the fairness and/or security in these protocols.
In this paper, we formalise a new property, delivery-fairness, to quantify the advantage. In particular, we distinguish two aspects of delivery-fairness, namely length-advantage, i.e., how many random outputs an adversary can learn earlier than correct participants, and time-advantage, i.e., how much time an adversary can learn a given random output earlier than correct participants. In addition, we prove the lower bound of delivery-fairness showing optimal guarantee. We further analyse the delivery-fairness guarantee of state-of-the-art DRBs and discuss insights, which, we show through case studies, could help improve delivery-fairness of existing systems to its optimal
RandChain: A Scalable and Fair Decentralised Randomness Beacon
We propose RANDCHAIN, a Decentralised Randomness Beacon (DRB) that is the first to achieve both scalability (i.e., a large number of participants can join) and fairness (i.e., each participant controls comparable power on deciding random outputs). Unlike existing DRBs where participants are collaborative, i.e., aggregating their local entropy into a single output, participants in RANDCHAIN are competitive, i.e., competing with each other to generate the next output. The competitive design reduces the communication complexity from at least O(n2) to O(n) without trusted party, breaking the scalability limit in existing DRBs.
To build RANDCHAIN, we introduce Sequential Proof-of-Work (SeqPoW), a cryptographic puzzle that takes a random and unpredictable number of sequential steps to solve. We implement RANDCHAIN and evaluate its performance on up to 1024 nodes, demonstrating its superiority (1.3 seconds per output with a constant bandwidth of 200KB/s per node) compared to state-of-the-art DRBs RandHerd (S&P’18) and HydRand (S&P’20)
Analysing and Improving Shard Allocation Protocols for Sharded Blockchains
Sharding is a promising approach to scale permissionless blockchains. In a sharded blockchain, participants are split into groups, called shards, and each shard only executes part of the workloads. Despite its wide adoption in permissioned systems, transferring such success to permissionless blockchains is still an open problem. In permissionless networks, participants may join and leave the system at any time, making load balancing challenging. In addition, the adversary in such networks can launch the single-shard takeover attack by compromising a single shard’s consensus. To address these issues, participants should be securely and dynamically allocated into different shards. However, the protocol capturing such functionality – which we call shard allocation – is overlooked.
In this paper, we study shard allocation protocols for permissionless blockchains. We formally define the shard allocation protocol and propose an evaluation framework. We apply the framework to evaluate the shard allocation subprotocols of seven state-of-the-art sharded blockchains, and show that none of them is fully correct or achieves satisfactory performance. We attribute these deficiencies to their extreme choices between two performance metrics: self-balance and operability. We observe and prove the fundamental trade-off between these two metrics, and identify a new property memory-dependency that enables parameterisation over this trade-off. Based on these insights, we propose Wormhole, a correct and efficient shard allocation protocol with minimal security assumptions and parameterisable self-balance and operability. We implement Wormhole and evaluate its overhead and performance metrics in a network with 128 shards and 32768 nodes. The results show that Wormhole introduces little overhead, achieves consistent self-balance and operability with our theoretical analysis, and allows the system to recover quickly from load imbalance
Reputation-based state machine replication
State machine replication (SMR) allows nodes to
jointly maintain a consistent ledger, even when a part of nodes
are Byzantine. To defend against and/or limit the impact of
attacks launched by Byzantine nodes, there have been proposals
that combine reputation mechanisms to SMR, where each node
has a reputation value based on its historical behaviours, and
the node’s voting power will be proportional to its reputation.
Despite the promising features of reputation-based SMR, existing
studies do not provide formal treatment on the reputation
mechanism on SMR protocols, including the types of behaviours
affecting the reputation, the security properties of the reputation
mechanism, or the extra security properties of SMR using
reputation mechanisms.
In this paper, we provide the first formal study on the
reputation-based SMR. We define the security properties of the
reputation mechanism w.r.t. these misbehaviours. Based on the
formalisation of the reputation mechanism, we formally define the
reputation-based SMR, and identify a new property reputationconsistency that is necessary for ensuring reputation-based SMR’s
safety. We then design a simple reputation mechanism that
achieves all security properties in our formal model. To demonstrate the practicality, we combine our reputation mechanism to
the Sync-HotStuff SMR protocol, yielding a simple and efficient
reputation-based SMR at the cost of only an extra ∆ in latency,
where ∆ is the maximum delay in synchronous networks
Fact and Fiction: Challenging the Honest Majority Assumption of Permissionless Blockchains
Honest majority is the key security assumption of Proof-of-Work (PoW) based blockchains. However, the recent 51% attacks render this assumption unrealistic in practice. In this paper, we challenge this assumption against rational miners in the PoW-based blockchains in reality. In particular, we show that the current incentive mechanism may encourage rational miners to launch 51% attacks in two cases. In the first case, we consider a miner of a stronger blockchain launches 51% attacks on a weaker blockchain, where the two blockchains share the same mining algorithm. In the second case, we consider a miner rents mining power from cloud mining services to launch 51% attacks. As 51% attacks lead to double-spending, the miner can profit from these two attacks. If such double-spending is more profitable than mining, miners are more intended to launch 51% attacks rather than mine honestly.
We formally model such behaviours as a series of actions through a Markov Decision Process. Our results show that, for most mainstream PoW-based blockchains, 51% attacks are feasible and profitable, so profit-driven miners are incentivised to launch 51% attacks to gain extra profit. In addition, we leverage our model to investigate the recent 51% attack on Ethereum Classic (on 07/01/2019), which is suspected to be an incident of 51% attacks. We provide insights on the attacker strategy and expected revenue, and show that the attacker’s strategy is near-optimal
On the Security and Performance of Blockchain Sharding
In this paper, we perform a comprehensive evaluation on blockchain sharding protocols. We deconstruct the blockchain sharding protocol into four foundational layers with orthogonal functionalities, securing some properties. We evaluate each layer of seven state-of-the-art blockchain sharding protocols, and identify a considerable number of new attacks, questionable design trade-offs and some open challenges. The layered evaluation allows us to unveil security and performance problems arising from a fundamental design choice, namely the coherence of system settings across layers. In particular, most sharded blockchains use different trust and synchrony assumptions across layers, without corresponding architectural guarantees. Unless a hybrid architecture were used, assuming differentiated system settings across layers can introduce subtle but severe failure syndromes or reduce the system’s performance
DACP: Enforcing a dynamic access control policy in cross-domain environments Item
Enabling hybrid authorisations to enforce dynamic access control policy from single-domain to cross-domain environments (CDEs) is important for distributed services. However, traditional Attribute-Based Access Control (ABAC) models are incompatible with CDEs. To fill this gap, approaches that apply cryptographic primitives, e.g., attribute-based encryption (ABE), have been proposed. The computation and storage overhead in most ABE constructions is non-negligible and increases with the complexity of the associated policies. In addition, most access control policy systems enforce authorisation policies in a centralized way, raising serious security and privacy issues. In this paper, we introduce DACP – a practical Dynamic Access Control Policy system supporting dynamic cross-domain authorisation. DACP combines traditional ABAC approach and a novel cryptographic primitive Attribute-based group signature (ABGS). ABAC is used for the access control decision and policy enforcement according to the user’s attributes whereas ABGS is used for managing the user’s attributes between users and authorities. Thus, the user’s attributes are securely distributed along with the access structure in CDEs while preserving the user’s privacy. We present the concrete design and implementation of DACP, and evaluate it in real-world settings. The evaluation shows that DACP is practical and efficient in CDEs.</p