This article provides a novel method to solve continuous-time semi-Markov processes by algorithms from discrete-time case, based on the fact that the Markov renewal function in discrete-time case is a finite series. Bounds of approximate errors due to discretization for the transition function matrix of the continuous-time semi-Markov process are investigated. This method is applied to a reliability problem which refers to the availability analysis of the system subject to sequential cyber-attacks. Two cases where sojourn times follow exponential and Weibull distributions are considered and computed in order to verify and illustrate the proposed method.

Using Semi-Markov Chains to Solve Semi-Markov Processes

Data-theoretic approach for socio-technical risk analysis: Text mining licensee event reports of U.S. nuclear power plants

Probabilistic modeling and analysis of sequential cyber-attacks

Due to rapid advancements on the Internet of Things (IoT), unmanned aerial vehicles (UAVs), also known as drones, are transforming numerous military and civil application areas. UAVs aim to enhance the production efficiency, ensure safety, and reduce risk, particularly protecting the human workforce in the case of harsh and dangerous environments. Due to the mission-critical, business-critical, or safety-critical nature of the UAV applications, it is pivotal that UAVs perform reliably to deliver the required service during the intended mission time. Therefore, reliability is one of the essential requirements for designing and operating UAVs. This article presents a critical review of UAV reliability literature in both theoretical and practical research, pinpointing failure causes and reliability challenges of UAV systems, classifying and reflecting on the reliability modeling, analysis, and design methods for UAV systems and key subsystems. Some open research problems and opportunities are also discussed to highlight potential new challenges for designing reliable and resilient UAVs and UAV-assisted IoT systems.

Reliability Theory and Practice for Unmanned Aerial Vehicles

The rising automation level and development of the Industry 4.0 concept in the mining sector increase the risk of cyber-attacks. As a result, this article focuses on developing a risk analysis method that integrates Kaplan’s and Garrick’s approach and fuzzy theory. The proposed approach takes into account the level of automation of the operating mining processes. Moreover, it follows five main steps, including identifying the automation level in a selected mine, definition of cyber-attack targets, identification of cyber-attack techniques, definition of cyber-attack consequences, and risk ratio assessment. The proposed risk assessment procedure was performed according to three cyber-attack targets (databases, internal networks, machinery) and seven selected types of cyber-attack techniques. The fuzzy theory is implemented in risk parameter estimation for cyber-attack scenario occurrence in the mining industry. To illustrate the given method’s applicability, seven scenarios for three levels of mine automation are analyzed. The proposed method may be used to reveal the current cybersecurity status of the mine. Moreover, it will be a valuable guide for mines in which automation is planned in the near future.

https://www.mdpi.com/1424-8220/20/24/7210/pdf

Cyber-Attacks Risk Analysis Method for Different Levels of Automation of Mining Processes in Mines Based on Fuzzy Theory Use

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. KeywordsBitcoin, Blockchain, Eclipse attack, Markov chain, Dependability analysis.

https://www.ijmems.in/volumes/volume6/number2/28-IJMEMS-20-118-6-2-469-479-2021.pdf

Dependability Analysis of Bitcoin subject to Eclipse Attacks

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. KeywordsBitcoin, Block chain, Dependability, Eclipse attack, Semi-Markov process (SMP).

https://www.ijmems.in/volumes/volume6/number2/29-IJMEMS-20-138-6-2-480-492-2021.pdf

Semi-Markov Based Dependability Modeling of Bitcoin Nodes Under Eclipse Attacks and State-Dependent Mitigation

https://onlinelibrary.wiley.com/doi/pdf/10.1002/qre.2845

A behavior-driven reliability modeling method for complex smart systems

With advances and globalization of information technology such as big data and cloud computing, topics about potential risks with security vulnerabilities have been brought to the forefront. Considerable efforts have been made to estimate network security risk with an unlimited cycle of disclosed vulnerabilities in the form of threats or attacks and managements to migrate these risks. On the other hand, reliability is often considered as one of the most vital factors that affect functions of critical computing systems. In this work, we explore a framework for considering both security and reliability risks, where their causes and effects are investigated. Risk assessment considering both security and reliability is then demonstrated through a case study, where a cloud RAID (redundant array of independent disks) storage system under DoS (denial-of-service) attacks is modeled and analyzed using an analytical method integrating Markov chains and binary decision diagrams.

Qisi Liu

Papers

Probabilistic modeling and analysis of sequential cyber-attacks

Dependability Analysis of Bitcoin subject to Eclipse Attacks

Semi-Markov Based Dependability Modeling of Bitcoin Nodes Under Eclipse Attacks and State-Dependent Mitigation

A behavior-driven reliability modeling method for complex smart systems

Framework of Probabilistic Risk Assessment for Security and Reliability