Deokyoon Ko’s research while affiliated with Seoul Semiconductor Co. and other places

As a future game-changer in various industries, cryptocurrency is attracting people’s attention. Cryptocurrency is issued on blockchain and managed through a blockchain wallet application. The blockchain wallet manages user’s digital assets and authenticates a blockchain user by checking the possession of a user’s private key. The mnemonic code technique represents the most widely used method of generating and recovering a private key in blockchain wallet applications. However, the mnemonic code technique does not consider usability to generate and recover a user’s private key. In this study, we propose a novel approach for private key generation and recovery. Our approach is based on the idea that a user can hold long-term memory from distinctive pictures. The user can generate a private key by providing pictures and the location of the pictures. For recovering a private key, the user identifies the locations of the pictures that are used in the private key generation process. In this paper, we experiment with the security and usability of our approach and confirm that our proposed approach is sufficiently secure compared to the mnemonic code technique and accounts for usability.

The Internet of Things uses low-power wireless communication for wireless connectivity and efficient energy. Low-power wireless communication is applied to IoT for wireless connection and efficient energy consumption in various areas such as wearable devices, smart homes, and power plants in order to send and receive data and control the environment. Security is becoming more important because the Internet of Things controls real physical systems. For the security of the Internet of Things, the encryption key is important to identify and authenticate devices that are trusted. The static encryption key method used for devices is likely to be calculated in reverse through the value of the key and is vulnerable to exploitation attacks. This requires the application of dynamic encryption keys that generate keys periodically. However, in the case of low-power wireless communication, the asynchronous communication method and the packet loss make it difficult to apply existing dynamic encryption key technologies. In this paper, we proposed dynamic encryption key method that applies the mechanism of the block chain to solve these problems. Based on the history of sensor data between devices, encryption keys are dynamically generated. The proposed method is to generate the same encryption key between devices with only one step of asynchronous communication considering packet loss. The proposed method is also validated in terms of availability and security in the Internet of Things low-power wireless communication.

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.

Completeness is one of the key attributes for a high-quality software requirements specification. Although incomplete requirements frequently occur in the requirements specification, it is rarely discovered. This turns out to be one of the major causes of software project failure. In order to handle this issue, this paper proposes an automatic approach to recommending omitted steps in a use case-based requirements specification. First, we automatically extract diverse scenario patterns by using the verb clustering algorithm and scenario flow graphs. Based on the scenario patterns, our approach detects omitted steps of user’s scenarios by the pattern matching algorithm and automatically recommends appropriate steps for the omitted parts. For validation of our approach, we have developed tool support, named ScenarioAmigo, and collected 231 use case specifications composing of 1874 scenario steps from 12 academic or proprietary projects. We first carried out the preliminary study to decide appropriate thresholds and weights. Then, we conducted three experiments as a quantitative performance evaluation. First, the cross-validation for the collected scenarios shows the 76% precision and 80% recall. Second, the comparison of recall of ScenarioAmigo to that of human experts obtained the 20% higher score. As the last experiment, we compared the result of ScenarioAmigo and human experts in terms of severity of each scenario and found that our approach could recommend normal as well as important scenarios, compared to the human experts.

Blockchain is a decentralized transaction and data management technology developed first for Bitcoin cryptocurrency. The interest in Blockchain technology has been increasing since the idea was coined in 2008. The reason for the interest in Blockchain is its central attributes that provide security, anonymity and data integrity without any third party organization in control of the transactions, and therefore it creates interesting research areas, especially from the perspective of technical challenges and limitations. In this research, we have conducted a systematic mapping study with the goal of collecting all relevant research on Blockchain technology. Our objective is to understand the current research topics, challenges and future directions regarding Blockchain technology from the technical perspective. We have extracted 41 primary papers from scientific databases. The results show that focus in over 80% of the papers is on Bitcoin system and less than 20% deals with other Blockchain applications including e.g. smart contracts and licensing. The majority of research is focusing on revealing and improving limitations of Blockchain from privacy and security perspectives, but many of the proposed solutions lack concrete evaluation on their effectiveness. Many other Blockchain scalability related challenges including throughput and latency have been left unstudied. On the basis of this study, recommendations on future research directions are provided for researchers.

The full list of selected primary papers. (PDF)

PRISMA Checklist. (DOC)

PRISMA Flow diagram. (DOC)

Completeness in software requirements specification is one of the key factors for successful software development. For specifying software requirements, scenario-based approach is broadly used, comprising a basic flow regarding the successful use of the system, and alternative flows describing abnormal or less frequent interactions of the system. However, alternative flows tend to be frequently missed in many cases, because of the relative lower significance rather than the basic flow, which eventually have an influence on achieving the completeness of software requirements. In order to address the issue, we propose an approach for automatically recommending alternative flows from a basic flow by extracting the essential use case patterns based on the occurrence patterns of the agents and measuring the verb similarity between the main verbs of each scenario. In order to validate our approach, we apply it to three industrial case studies, and show comprehensiveness of the suggested alternative flows and synergic effectiveness for inexperienced developers.

Software requirement analysis is necessary for successful software development project. Specially, incomplete requirement is the most influential causes of software project failure. Incomplete requirement can bring late delay and over budget because of the misunderstanding and ambiguous criteria for project validation. Software requirement patterns can help writing more complete requirement. These can be a reference model and standards when author writing or validating software requirement. Furthermore, when a novice writes the software scenario, the requirement patterns can be one of the guideline. In this paper proposes an automatic approach to identifying software scenario patterns from various software scenarios. In this paper, we gathered 83 scenarios from eight industrial systems, and show how to extract 54 scenario patterns and how to find omitted action of the scenario using extracted patterns for the feasibility of the approach.