The security of Bitcoin protocols is deeply dependent on the incentives provided to miners, which come from a combination of block rewards and transaction fees. As Bitcoin experiences more halving events, the protocol reward converges to zero, making transaction fees the primary source of miner rewards. This shift in Bitcoin's incentivization mechanism, which introduces volatility into block rewards, leads to the emergence of new security threats or intensifies existing ones. Previous security analyses of Bitcoin have either considered a fixed block reward model or a highly simplified volatile model, overlooking the complexities of Bitcoin's mempool behavior.

Validators in permissionless, large-scale blockchains, such as Ethereum, are typically payoff-maximizing, rational actors. Ethereum relies on in-protocol incentives, like rewards for correct and timely votes, to induce honest behavior and secure the blockchain. However, external incentives, such as the block proposer’s opportunity to capture maximal extractable value (MEV), may tempt validators to deviate from honest protocol participation.We show a series of commitment attacks on LMD GHOST, a core part of Ethereum’s consensus mechanism. We demonstrate how a single adversarial block proposer can orchestrate long-range chain reorganizations by manipulating Ethereum’s reward system for timely votes. These attacks disrupt the intended balance of power between proposers and voters: by leveraging credible threats, the adversarial proposer can coerce voters from previous slots into supporting blocks that conflict with the honest chain, enabling a chain reorganization.In response, we introduce a novel reward mechanism that restores the voters’ role as a check against proposer power. Our proposed mitigation is fairer and more decentralized – not only in the context of these attacks – but also practical for implementation in Ethereum.

A Bitcoin miner who owns a sufficient amount of mining power can perform selfish mining to increase its relative revenue. Studies have demonstrated that the time-averaged profit of a selfish miner starts to rise once the mining difficulty level gets adjusted in favor of the attacker. Selfish mining profitability lies in the fact that orphan blocks are not incorporated into the current version of Bitcoin’s difficulty adjustment mechanism (DAM). Therefore, it is believed that considering the count of orphan blocks in the DAM can result in complete unprofitability for selfish mining. In this paper, we disprove this belief by providing a formal analysis of the selfish mining time-averaged profit. We present a precise definition of the orphan blocks that can be incorporated into calculating the next epoch’s target and then introduce two modified versions of DAM in which both main-chain blocks and orphan blocks are incorporated. We propose two versions of smart intermittent selfish mining, where the first one dominates the normal intermittent selfish mining, and the second one results in selfish mining profitability under the modified DAMs. Moreover, we present the orphan exclusion attack with the help of which the attacker can stop honest miners from reporting the orphan blocks. Using combinatorial tools, we analyze the profitability of selfish mining accompanied by the orphan exclusion attack under the modified DAMs. Our results show that even when considering orphan blocks in the DAM, selfish mining can still be profitable. However, the level of profitability under the modified DAMs is significantly lower than that observed under the current version of Bitcoin DAM, suggesting that orphan reporting can be an effective countermeasure against a payoff-maximizing selfish miner.

Rapid technological advancements in unmanned aerial vehicles (UAVs) have revolutionized intelligent platforms such as smart cities. These advancements have paved the way for an emerging class of Internet of Things (IoT) systems called the Internet of Drones (IoD), which has noteworthy security and privacy challenges. In this article, we tackle the problem of secure logging and design a novel secure logging scheme—DASLog—for the use case of aerial transport of (medical) goods via drones. Our logging scheme provides public auditability of logging records in the setting where all logging components are managed by a single entity. Our secure logging system relies on hash chains and a Merkle tree to generate proofs for stored logging records. These proofs get written on a private blockchain and can be used later by data consumers to verify the integrity and completeness of a set of logging records. We demonstrate the feasibility of our approach via a proof-of-concept prototype relying on Hyperledger Besu and implemented on multiple Amazon EC2 instances. The performance evaluation of our demonstrator shows that up to 8000 logging records per second can be processed.

This paper explores the applications of Distributed Ledger Technologies (DLTs) in Peer-to-Peer (P2P) electricity trading. It highlights the challenges and trade-offs of applying three different DLTs: Blockchain, Directed Acyclic Graph (DAG), and Holochain. First, the study introduces the energy transition concept in the smart city context. Second, P2P electricity trading and its supporting trading mechanisms are introduced. Third, DLTs are defined and three different types of DLTs are introduced. Forth, possibilities, challenges, and consequences of applying DLTs in electricity trading are explained. Last, applying DLTs for P2P electricity trading from different aspects are discussed. This paper provides a benchmark for applying DLTs to foster energy transition in smart cities. It highlights how this type of technology can serve smart circular economy.