Information technology (IT) security has become a major concern due to the growing demand for information and massive development of client/server applications for various types of applications running on modern IT infrastructure. How has security been taken into account and which paradigms are necessary to minimize security issues while increasing efficiency, reducing the influence on transmissions, ensuring protocol independency and achieving substantial performance? We have found cryptography to be an absolute security mechanism for client/server architectures, and in this study, a new security design was developed with the MODBUS protocol, which is considered to offer phenomenal performance for future development and enhancement of real IT infrastructure. This study is also considered to be a complete development because security is tested in almost all ways of MODBUS communication. The computed measurements are evaluated to validate the overall development, and the results indicate a substantial improvement in security that is differentiated from conventional methods.

A software defect prediction (SDP) model identifies the defect-prone modules. Setting appropriate parameters in an SDP model is critical because it affects the model performance. In a recent study, parameters were automatically explored using an optimization algorithm. However, such studies did not explore all the parameters that could be handled in the SDP process from preprocessing to model building, but only optimized parameters in some modeling process steps, such as feature selection or model building. Our goal is to improve the model performance by optimizing parameters across the entire SDP process. For this, we propose a cost-sensitive decision tree based on harmony search (HS-CSDT). HS-CSDT uses a harmony search algorithm to simultaneously identify the optimal feature set, regularization technique, class weight, and decision tree hyperparameters. We compared HS-CSDT against the methods in related studies in terms of probability of detection, probability of false alarm, G-measure, and file inspection reduction in the evaluation of 28 open-source projects. The results of the effect size using Cohen’s d reveal that HS-CSDT provides a statistically better performance than methods in related work. Experimental results show that optimizing the identified parameters throughout the entire SDP modeling process by using the optimization algorithm helps improve the model performance. In summary, HS-CSDT shows excellent defect prediction performance by automatically allocating an appropriate parameter set according to the software project. Thus, the model can help effectively allocate limited quality assurance resources.

Recently, organizations face various business challenges because of rapidly changing user needs and expectations. SOA (Service-Oriented Architecture) is a promising technique for adequately handling them in organizations. In developing SOA based systems, service identification is one of the core activities, having a broad influence on the systems. To identify proper services, business goals and business change factors should be analyzed because the ultimate aim of SOA is to achieve business goals and business agility in turbulent business environment. To tackle this, we propose a service identification method based on goal-scenario modeling and a conceptual framework to elicit possible business changes. Traceability among business goals, business changes and identified services are also constructed in this approach. We applied our approach into the HRS (Hotel Reservation System) domain to demonstrate its feasibility.

Among various consensus algorithms, the Byzantine Fault Tolerance (BFT)-based consensus algorithms are broadly used for private blockchain. However, as BFT-based consensus algorithms are structured for all participants to take part in a consensus process, a scalability issue becomes more noticeable. In this approach, we introduce a consensus coordinator to execute a conditionally BFT-based consensus algorithm by classifying transactions. Transactions are divided into equal and unequal transactions. Moreover, unequal transactions are divided again and classified as common and trouble transactions. After that, a consensus algorithm is only executed for trouble transactions, and BFT-based consensus algorithms can achieve scalability. For evaluating our approach, we carried out three experiments in response to three research questions. By applying our approach to PBFT, we obtained 4.75 times better performance than using only PBFT. In the other experiment, we applied our approach to IBFT of Hyperledger Besu, and our result shows a 61.81% performance improvement. In all experiments depending on the change of the number of blockchain nodes, we obtained the better performance than original BFT-based consensus algorithms; thus, we can conclude that our approach improved the scalability of original BFT-based consensus algorithms. We also showed a correlation between performance and trouble transactions associated with transaction issue intervals and the number of blockchain nodes.