Nakamoto consensus is prevailing in the world largest blockchain-based cryptocurrency systems, such as Bitcoin and Ethereum. Since then, various attempts have been studied to attack Nakamoto consensus worldwide. In recent years, network delay has won more attention for making inconsistent ledgers in blockchain-based applications by virtue of attacking Nakamoto consensus. However, so far as we know, most of the existing works mainly focus on constructing inconsistent ledgers for blockchain systems, but not offering fine-grained theoretical analysis for how to optimize the success probability by flexibly dividing computational power and network delay from the viewpoint of adversary. The paper first utilizes network delay and the partition of controlled computation power of honest miners for making forks as long as possible. Then, formally analysis is provided to show the success probability of the proposed attack, and compute the optimal network delay and splitting for adversarial computation power in theory. Finally, simulation experiments validate the correctness of the formal analysis.

Recent results show that the differential properties within quadruples boom as a new inspiration in cryptanalysis of Advanced Encryption Standard (AES)-like constructions. These methods include the exchange attack proposed in Asiacrypt’19, the mixture differential attack proposed in ToSC’18, etc., where the essential properties are obtained by manually scrutinizing the structures of the AES-like constructions. This paper presents a novel framework and an automatic tool based on mixed integer linear programming to search for mixture differential distinguishers for general constructions. This framework considers what equality patterns among quadruples can make a distinguisher and traces how the patterns propagate through cipher components with accurate probability estimation. With this tool, a 5-round AES distinguishing attack with lower complexity and more 6-round distinguishing attacks in the chosen plaintext scenarios are deduced. We prove that no exchange-type or mixture differential distinguisher exists for 7 and above rounds AES if the details of the Sbox and MixColumns matrix are not taken into account.

To date, bitcoin has been the most successful application of blockchain technology and has received considerable attention from both industry and academia. Bitcoin is an electronic payment system based on cryptography rather than on credit. Regardless of whether people are in the same city or country, bitcoin can be sent by any one person to any other person when they reach an agreement. The market value of bitcoin has been rising since its advent in 2009, and its current market value is US160 billion. Since its development, bitcoin itself has exposed many problems and is facing challenges from all the sectors of society; therefore, adversaries may use bitcoin’s weakness to make considerable profits. This survey presents an overview and detailed investigation of data security and privacy in bitcoin system. We examine the studies in the literature/Web in two categories: 1) analyses of the attacks to the privacy, availability, and consistency of bitcoin data and 2) summaries of the countermeasures for bitcoin data security. Based on the literature/Web, we list and describe the research methods and results for the two categories. We compare the performance of these methods and illustrate the relationship between the performance and the methods. Moreover, we present several important open research directions to identify the follow-up studies in this area.

With the development of network technology and cloud computing, data sharing is becoming increasingly popular, and many scholars have conducted in-depth research to promote its flourish. As the scale of data sharing expands, its privacy protection has become a hot issue in research. Moreover, in data sharing, the data is usually maintained in multiple parties, which brings new challenges to protect the privacy of these multi-party data. In this paper, we propose a trusted data sharing scheme using blockchain. We use blockchain to prevent the shared data from being tampered, and use the Paillier cryptosystem to realize the confidentiality of the shared data. In the proposed scheme, the shared data can be traded, and the transaction information is protected by using the (p, t)-threshold Paillier cryptosystem. We conduct experiments in cloud storage scenarios and the experimental results demonstrate the efficiency and effectiveness of the proposed scheme.