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 pine sawyer beetle Monochamus alternatus Hope, a major forest insect pest, is the primary vector of the destructive forest pest pine wood nematode, Bursaphelenchus xylophilus. Azadirachtin, an active compound of neem, is biologically interesting because it represents a group of important, successful botanical pesticides. We provide insight into the molecular effects of azadirachtin on M. alternatus at the transcriptional level to provide clues about possible molecular-level targets and to establish a link between azadirachtin and insect global responses. We found that 920 and 9894 unique genes were significantly up- and down-regulated, respectively. We obtained expression patterns of the differentially expressed genes (DEGs), identifying 4247, 3488 and 7613 sequences that involved cellular components, molecular functions and biological processes, respectively, and showed that the DEGs were distributed among 50 Gene Ontology categories. The Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that the DEGs were enriched in 50 pathways. Detailed gene profile knowledge of the interaction of azadirachtin with M. alternatus should facilitate the development of more effective azadirachtin-based products against M. alternatus and other target Coleoptera. These results further enhance the value of azadirachtin as a potential insecticide of biological origin, as well as for other biological applications.

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With recent advancements in Internet technologies and wireless communications, wireless sensor network (WSN)‐based smart systems are gaining an enormous increase in use in various applications (eg, healthcare, smart home, smart manufacturing, smart power grids, and smart transportation). Due to the mission‐critical or safety‐critical nature of smart system applications, it is imperative that a smart system be reliable during its mission time. However, reliability analysis and design of smart systems are still open challenging research problems due to complicated dependencies existing in the WSN domain or the physical domain monitored by the WSN, and due to dependencies crossing the two domains. This paper proposes a new behavior‐driven reliability modeling methodology for accurate and efficient reliability analysis of complex WSN‐based smart systems, contributing toward their robust designs and operations. The suggested method can address effects of dependent behaviors affecting different domains of the smart system in a combinatorial manner. It also enables the use of efficient single‐domain reliability methods to retain their efficiency. A case study of a smart home system is performed to demonstrate the application of the proposed method as well as its advantages in handling nonexponential time‐to‐failure distributions and in analyzing smart systems with complicated intradomain and cross‐domain dependencies.

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.