Daniël Reijsbergen

Daniel Reijsbergen, Aung Maw, Tien Tuan Anh Dinh et al.

Smart grids leverage the data collected from smart meters to make important operational decisions. However, they are vulnerable to False Data Injection (FDI) attacks in which an attacker manipulates meter data to disrupt the grid operations. Existing works on FDI are based on a simple threat model in which a single grid operator has access to all the data, and only some meters can be compromised. Our goal is to secure smart grids against FDI under a realistic threat model. To this end, we present a threat model in which there are multiple operators, each with a partial view of the grid, and each can be fully compromised. An effective defense against FDI in this setting is to share data between the operators. However, the main challenge here is to incentivize data sharing. We address this by proposing an incentive mechanism that rewards operators for uploading data, but penalizes them if the data is missing or anomalous. We derive formal conditions under which our incentive mechanism is provably secure against operators who withhold or distort measurement data for profit. We then implement the data sharing solution on a private blockchain, introducing several optimizations that overcome the inherent performance limitations of the blockchain. Finally, we conduct an experimental evaluation that demonstrates that our implementation has practical performance.

Daniel Reijsbergen, Zheng Yang, Aung Maw et al.

Smart grids leverage data from smart meters to improve operations management and to achieve cost reductions. The fine-grained meter data also enable pricing schemes that simultaneously benefit electricity retailers and users. Our goal is to design a practical dynamic pricing protocol for smart grids in which the rate charged by a retailer depends on the total demand among its users. Realizing this goal is challenging because neither the retailer nor the users are trusted. The first challenge is to design a pricing scheme that incentivizes consumption behavior that leads to lower costs for both the users and the retailer. The second challenge is to prevent the retailer from tampering with the data, for example, by claiming that the total consumption is much higher than its real value. The third challenge is data privacy, that is, how to hide the meter data from adversarial users. To address these challenges, we propose a scheme in which peak rates are charged if either the total or the individual consumptions exceed some thresholds. We formally define a privacy-preserving transparent pricing scheme (PPTP) that allows honest users to detect tampering at the retailer while ensuring data privacy. We present two instantiations of PPTP, and prove their security. Both protocols use secure commitments and zero-knowledge proofs. We implement and evaluate the protocols on server and edge hardware, demonstrating that PPTP has practical performance at scale.

Stefanos Leonardos, Barnabé Monnot, Daniël Reijsbergen et al.

Participation in permissionless blockchains results in competition over system resources, which needs to be controlled with fees. Ethereum's current fee mechanism is implemented via a first-price auction that results in unpredictable fees as well as other inefficiencies. EIP-1559 is a recent, improved proposal that introduces a number of innovative features such as a dynamically adaptive base fee that is burned, instead of being paid to the miners. Despite intense interest in understanding its properties, several basic questions such as whether and under what conditions does this protocol self-stabilize have remained elusive thus far. We perform a thorough analysis of the resulting fee market dynamic mechanism via a combination of tools from game theory and dynamical systems. We start by providing bounds on the step-size of the base fee update rule that suffice for global convergence to equilibrium via Lyapunov arguments. In the negative direction, we show that for larger step-sizes instability and even formally chaotic behavior are possible under a wide range of settings. We complement these qualitative results with quantitative bounds on the resulting range of base fees. We conclude our analysis with a thorough experimental case study that corroborates our theoretical findings.

Bithin Alangot, Daniel Reijsbergen, Sarad Venugopalan et al.

Clients of permissionless blockchain systems, like Bitcoin, rely on an underlying peer-to-peer network to send and receive transactions. It is critical that a client is connected to at least one honest peer, as otherwise the client can be convinced to accept a maliciously forked view of the blockchain. In such an eclipse attack, the client is unable to reliably distinguish the canonical view of the blockchain from the view provided by the attacker. The consequences of this can be catastrophic if the client makes business decisions based on a distorted view of the blockchain transactions. In this paper, we investigate the design space and propose two approaches for Bitcoin clients to detect whether an eclipse attack against them is ongoing. Each approach chooses a different trade-off between average attack detection time and network load. The first scheme is based on the detection of suspicious block timestamps. The second scheme allows blockchain clients to utilize their natural connections to the Internet (i.e., standard web activity) to gossip about their blockchain views with contacted servers and their other clients. Our proposals improve upon previously proposed eclipse attack countermeasures without introducing any dedicated infrastructure or changes to the Bitcoin protocol and network, and we discuss an implementation. We demonstrate the effectiveness of the gossip-based schemes through rigorous analysis using original Internet traffic traces and real-world deployment. The results indicate that our protocol incurs a negligible overhead and detects eclipse attacks rapidly with high probability, and is well-suited for practical deployment.

Daniel Reijsbergen, Pawel Szalachowski, Junming Ke et al.

We present Large-scale Known-committee Stake-based Agreement (LaKSA), a chain-based Proof-of-Stake protocol that is dedicated, but not limited, to cryptocurrencies. LaKSA minimizes interactions between nodes through lightweight committee voting, resulting in a simpler, more robust, and more scalable proposal than competing systems. It also mitigates other drawbacks of previous systems, such as high reward variance and long confirmation times. LaKSA can support large numbers of nodes by design, and provides probabilistic safety guarantees in which a client makes commit decisions by calculating the probability that a transaction is reverted based on its blockchain view. We present a thorough analysis of LaKSA and report on its implementation and evaluation. Furthermore, our new technique of proving safety can be applied more broadly to other Proof-of-Stake protocols.

Pieter Hartel, Ivan Homoliak, Daniël Reijsbergen

Since it takes time and effort to put a new product or service on the market, one would like to predict whether it will be a success. In general this is not possible, but it is possible to follow best practices in order to maximise the chance of success. A smart contract is intended to encode business logic and is therefore at the heart of every new business on the Ethereum blockchain. We have investigated how to measure the success of smart contracts, and whether successful smart contracts have characteristics that less successful smart contracts lack. The appearance of a smart contract on a listing website such as Etherscan or StateoftheDapps is such a characteristic. In this paper, we present a three-pronged analysis of the relative success of listed smart contracts. First, we have used statistical analysis on the publicly visible transaction history of the Ethereum blockchain to determine that listed contracts are significantly more successful than their unlisted counterparts. Next, we have conducted a survey among more than 200 developers via an anonymous online survey about their experience with the listing process. A significant majority of respondents do not believe that listing a contract itself contributes to its success, but they believe that the extra attention that is typically paid in tandem with the listing process does contribute. Finally, based on the respondents' answers, we have drafted 10 recommendations for developers and validated them by submitting them to an international panel of experts.

Pawel Szalachowski, Daniel Reijsbergen, Ivan Homoliak et al.

Bitcoin is the most successful cryptocurrency so far. This is mainly due to its novel consensus algorithm, which is based on proof-of-work combined with a cryptographically-protected data structure and a rewarding scheme that incentivizes nodes to participate. However, despite its unprecedented success Bitcoin suffers from many inefficiencies. For instance, Bitcoin's consensus mechanism has been proved to be incentive-incompatible, its high reward variance causes centralization, and its hardcoded deflation raises questions about its long-term sustainability. In this work, we revise the Bitcoin consensus mechanism by proposing StrongChain, a scheme that introduces transparency and incentivizes participants to collaborate rather than to compete. The core design of our protocol is to reflect and utilize the computing power aggregated on the blockchain which is invisible and "wasted" in Bitcoin today. Introducing relatively easy, although important changes to Bitcoin's design enables us to improve many crucial aspects of Bitcoin-like cryptocurrencies making it more secure, efficient, and profitable for participants. We thoroughly analyze our approach and we present an implementation of StrongChain. The obtained results confirm its efficiency, security, and deployability.

Stefanos Leonardos, Daniel Reijsbergen, Georgios Piliouras

Proof of Stake (PoS) protocols rely on voting mechanisms to reach consensus on the current state. If an enhanced majority of staking nodes, also called validators, agree on a proposed block, then this block is appended to the blockchain. Yet, these protocols remain vulnerable to faults caused by validators who abstain either accidentally or maliciously. To protect against such faults while retaining the PoS selection and reward allocation schemes, we study weighted voting in validator committees. We formalize the block creation process and introduce validators' voting profiles which we update by a multiplicative weights algorithm relative to validators' voting behavior and aggregate blockchain rewards. Using this framework, we leverage weighted majority voting rules that optimize collective decision making to show, both numerically and analytically, that the consensus mechanism is more robust if validators' votes are appropriately scaled. We raise potential issues and limitations of weighted voting in trustless, decentralized networks and relate our results to the design of current PoS protocols.

Vincent Chia, Pieter Hartel, Qingze Hum et al.

Blockchain technology has become almost as famous for incidents involving security breaches as for its innovative potential. We shed light on the prevalence and nature of these incidents through a database structured using the STIX format. Apart from OPSEC-related incidents, we find that the nature of many incidents is specific to blockchain technology. Two categories stand out: smart contracts, and techno-economic protocol incentives. For smart contracts, we propose to use recent advances in software testing to find flaws before deployment. For protocols, we propose the PRESTO framework that allows us to compare different protocols within a five-dimensional framework.

Daniël Reijsbergen, Rajeev Ratan

We propose a data-driven methodology for evaluating the impact of the introduction of a speed limit on the punctuality of bus services. In particular, we use high-frequency Automatic Vehicle Location data to parameterise a model that represents the movement of a bus along predefined patches of the route. We fit the probability distributions of the time spent in each patch to two classes of probability distributions: hyper-Erlang distributions, for which we use the tool HyperStar, and a variation of the three-parameter gamma distributions recommended by the Traffic Engineering Handbook. In both cases we obtain models that can be expressed using the framework of Probabilistic Timed Automata, allowing us to evaluate bus punctuality using the model checking tool UPPAAL. We conduct a case study involving a proposed speed limit in Edinburgh. This is an extended version of a paper presented at ValueTools 2015.