Security is one of the major challenges for promoting the computer industry. Existing models for assessing security have mostly assumed that different hazards causing the security breach are independent of each other. Dependencies however can exist among different hazardous actions and they may affect the system security attribute greatly. This paper advances the state of the art in quantitative security risk assessment by modeling one such dependency, where multiple sequence‐dependent hazardous actions are performed to launch a successful security cyber‐attack. Continuous‐time Markov chain and semi‐Markov process–based methods are proposed to estimate the occurrence probability of a security risk for systems undergoing the sequential cyber‐attacks. While the CTMC method is limited to the exponential state transition time, the proposed semi‐Markov process–based approach is applicable to analyzing attacks with any arbitrary types of transition time distributions. Both methods are illustrated using case studies where Trojan attacks in the banking application are modeled and analyzed.

The immense potential of the blockchain technology in diverse and critical applications (e.g., financial services, cryptocurrencies, supply chains, smart contracts, and automotive industry) has led to a new challenge: the dependability modeling and analysis of the blockchain-based systems. In this paper, we model the Bitcoin, a peer-to-peer cryptocurrency system built on the blockchain technology that allows individuals to trade freely without involving banks or other intermediate agents. We analyze the dependability of the Bitcoin system subject to the Eclipse attack. A continuous-time Markov chain-based method is suggested to model the system behavior under the Eclipse attack and further quantify the dependability of the Bitcoin system. The effects of several model parameters (related to the miner’s habits in system protection, restart, and mining frequency) on the system dependability are demonstrated through numerical examples. Findings from this work may provide effective guidelines in designing a resilient and robust Bitcoin system.

The block chain technology has immense potential in many different applications, including but not limited to cryptocurrencies, financial services, smart contracts, supply chains, healthcare services, and energy trading. Due to the critical nature of these applications, it is pivotal to model and evaluate dependability of the block chain-based systems, contributing to their reliable and robust operation. This paper models and analyzes the dependability of Bitcoin nodes subject to Eclipse attacks and state-dependent mitigation activities. Built upon the block chain technology, the Bitcoin is a peer-to-peer cryptocurrency system enabling an individual user to trade freely without the involvement of banks or any other types of intermediate agents. However, a node in the Bitcoin is vulnerable to the Eclipse attack, which aims to monopolize the information flow of the victim node. A semi-Markov process (SMP) based approach is proposed to model the Eclipse attack behavior and possible mitigation activities that may prevent the attack from being successful during the attack process. The SMP model is then evaluated to determine the steady-state dependability of the Bitcoin node. Numerical examples are provided to demonstrate the influence of the time to restart the Bitcoin software and time to detect and delete the malicious message on the Bitcoin node dependability.

Bitcoin is an electronic cryptocurrency developed based on Blockchain technology. With its decentralized feature, it has become incredibly popular since its invention. However, the Bitcoin network suffers from 51% attacks, where if malicious attackers’ control over half of the computing power, they are able to rewrite the network. The attackers are capable of doing so by initiating the Eclipse attack first, which aims to monopolize all communications from and to a controlled Bitcoin node. In this paper, we model and analyze the dependability of the Bitcoin network subject to the Eclipse and 51% attacks. We propose a hierarchical model that encompasses a continuous-time Markov chain method for the node-level dependability analysis and a multi-valued decision diagram method for the system-level dependability analysis. Detailed case studies on Bitcoin systems with homogeneous and heterogeneous nodes are conducted to demonstrate the proposed model and investigate the impacts of several critical parameters on Bitcoin network dependability.

Blockchain technology has gained prominence over the last decade. Numerous achievements have been made regarding how this technology can be utilized in different aspects of the industry, market, and governmental departments. Due to the safety-critical and security-critical nature of their uses, it is pivotal to model the dependability of blockchain-based systems. In this study, we focus on Bitcoin, a blockchain-based peer-to-peer cryptocurrency system. A continuous-time Markov chain-based analytical method is put forward to model and quantify the dependability of the Bitcoin system under selfish mining attacks. Numerical results are provided to examine the influences of several key parameters related to selfish miners’ computing power, attack triggering, and honest miners’ recovery capability. The conclusion made based on this research may contribute to the design of resilience algorithms to enhance the self-defense and robustness of cryptocurrency systems.