Sangsoo Kim

Myungrock Lee

Dohoon Kim

Donghyun Lee

Ryungchul Han

Changgyun Jeon

Youngseob Han

Taek Lee

Neunghoe Kim

Jongwook Jung

Jungbin Lee

MinGwan Kim

Seongrim Cho

Mpyana Mwamba Merlec

Sundeuk Kim

Jeongwook Chae

Heeseo Chae

Sangwon Im

Jiyong Park

Yeongyun Shin

Jinwoo Shin

Seungbin Kim

Sungjoon Park

Sunghoon Lee

Eunyoung Kim

Seungyong Shin

Jaehoon Kim

Taehoon Um

Jinyoung Lee

Yoongyu Lee

Dongmin Seo

Yunhui Park

Geunhyung Lee

Jungjin Choi

Sangeun Park

Joowon Kim

Andri

Chulhoon Byeon

Donghyun Kim

AL SHAIMA

Jaeyeon Lee

Jaeyong Park

Daegeon Lee

Hyunsik Jeon

Myungwoo Lee

Lovemore Ngwira

Dongwon Lee

Jace Jihyok Choi

Woojin Lee

Bongjun Kim

Md. Mainul Islam

Yongjun Kim

Sanghyun Lee

The Intelligent Blockchain Engineering Laboratory conducts research on blockchain technology and its applications.

지능형 블록체인 엔지니어링 연구실은 블록체인 기술 및 응용 분야에 대한 연구를 수행한다.

ZK-Sandbox: Zero-Knowledge Data Sandbox System for Enhancing End-to-End Security and Privacy of Verifiable Credentials

GNNRec: A Graph-Based Neural Network Model for Efficient and Robust Product Recommendation

Proof of Random Leader: A Fast and Manipulation-Resistant Proof-of-Authority Consensus Algorithm for Permissioned Blockchains Using Verifiable Random Function

Proof of Work with Random Selection (PoWR): An Energy Saving Consensus Algorithm with Proof of Work and the Random Selection Function

An Auditable, Privacy-Preserving, Transparent Unspent Transaction Output Model for Blockchain-Based Central Bank Digital Currency

Blockchain-Based Decentralized Storage Systems for Sustainable Data Self-Sovereignty: A Comparative Study

SC-CAAC: A Smart Contract-Based Context-Aware Access Control Scheme for Blockchain-Enabled IoT Systems

DataMesh+: A Blockchain-Powered Peer-to-Peer Data Exchange Model for Self-Sovereign Data Marketplaces

Performance evaluation of a quantum-resistant Blockchain: a comparative study with Secp256k1 and Schnorr

Q-RTOP: Quantum-Secure Random Transaction Ordering Protocol for Mitigating Maximal Extractable Value Attacks in Blockchains With a Priority Gas-Fee Policy

Decentralized Global Copyright System Based on Consortium Blockchain with Proof of Authority

Multitier Web System Reliability: Identifying Causative Metrics and Analyzing Performance Anomaly Using a Regression Model

A Privacy-Preserving Transparent Central Bank Digital Currency System Based on Consortium Blockchain and Unspent Transaction Outputs

B-GPS : Blockchain-based Global Positioning System for Improve Data Integrity and Reliability

A Consortium Blockchain-Based Secure and Trusted Electronic Portfolio Management Scheme

A Smart Contract-based Dynamic Consent Management System for Personal  Data Usage in Public Health Crisis

Design of Military Service Framework for Enabling Migration to Military SaaS Cloud Environment

Priority Determination to Apply Artificial Intelligence Technology in Military Intelligence Areas

Topic Modeling Based Warning Prioritization from Change Sets of Software Repository

Investigating the Relationship Between Mutants and Real Faults with Respect to Mutated Code

GUI information-based interaction logging and visualization for asynchronous usability testing

Overlap-aware rapid type analysis for constructing one-to-one matched call graphs in regression test selection

Development of model based on clock gene expression of human hair follicle cells to estimate circadian time

Detecting usability problems in mobile applications on the basis of dissimilarity in user behavior

Addendum to the Acknowledgements: Mood Prediction of Patients With Mood Disorders by Machine Learning Using Passive Digital Phenotypes Based on the Circadian Rhythm: Prospective Observational Cohort Study

Mood prediction of patients with mood disorders by machine learning using passive digital phenotypes based on the circadian rhythm: prospective observational cohort study

Adaptive kinetic scrolling: kinetic scrolling for large datasets on mobile devices

Measuring the Degree of Content Immersion in a Nonexperimental Environment Using a Portable EEG Device

EURECA: End‐user requirements engineering with collaborative animation

PALC: Preference Alignment via Logit Calibration

zkQML: Verifiable and Privacy-Preserving Inference for Quantum Machine Learning

PQCIF: Post-Quantum Cryptography Integration Framework for Securing Blockchain-enabled Internet of Medical Things

PDaaS: A Personal Data-as-a-Service Platform using Permissioned Blockchain and IPFS

A Blockchain-based Trustworthy and Secure Review System for Decentralized e-Portfolio Platforms

A Comparative Analysis of Proof-of-Authority Consensus Algorithms:  Aura vs Clique

SmartBuilder: A Block-Based Visual Programming Framework for Smart Contract Development

Towards Context-Aware Smart Contracts for Blockchain IoT Systems

Blockchain-based Quantum Federated Learning Framework for Privacy-Preserving Digital Product Passports (DPPs)

A Study on the Quantum and Post-Quantum Cryptography-based Blockchain Security Framework for IoMT and Its Extension to Digital Product Passports

Design of a Privacy-Preserving Blockchain System for Game Achievement Badge Verification in Play-to-Earn(P2E) Model

Blockchain Network for non-face-to-face Medical Service Environment of GDPR Focus

Blockchain Network for non-face-to-face Medical Service Environment of GDPR Focus,

Accessibility of Blockchain based Medical Information

Regulating Ethereum Account Authority Using Smart Contract

Internet of Blockchains (IoB): Towards Scalability and Interoperability for Cross-chain Values Exchange

Blockchain-based Secure and Trusted Data Trading Methods and Platform System

A Method for Generating a Ricardian Contract of a blockchain based on a formal specification supported by recording medium

System for portfolio management based on blockchain and blockchain-based portfolio management system integrated with recruitment platforms

Blockchain-based Smart Contract Writing Device and Method for Legal Contracts

Identifying quality-requirement conflicts

Micro interaction metrics for defect prediction

Adaptive integral manifold control of flexible joint robot manipulators

Selfish attacks and detection in cognitive radio ad-hoc networks

A smart contract-based dynamic consent management system for personal data usage under GDPR

Applying WinWin to quality requirements: a case study

Developer micro interaction metrics for software defect prediction

From requirements negotiation to software architectural decisions

A quality-based cost estimation model for the product line life cycle

A scheme for data confidentiality in cloud-assisted wireless body area networks

A comparative analysis of proof-of-authority consensus algorithms: Aura vs Clique

A security risk analysis model for information systems

A study of different coding styles affecting code readability

VIRE: Sailing a blue ocean with value-innovative requirements

SC-CAAC: A smart-contract-based context-aware access control scheme for blockchain-enabled IoT systems

Situation-aware contract specification language for middleware for ubiquitous computing

Aids for identifying conflicts among quality requirements

A consortium blockchain-based secure and trusted electronic portfolio management scheme

Hoh Peter In

Without a well-defined set of quality-attribute requirements, software projects are vulnerable to failure. The authors have developed QARCC, a knowledge-based tool that helps users, developers, and customers analyze requirements and identify conflicts among them.

There is a common belief that developers' behavioral interaction patterns may affect software quality. However, widely used defect prediction metrics such as source code metrics, change churns, and the number of previous defects do not capture developers' direct interactions. We propose 56 novel micro interaction metrics (MIMs) that leverage developers' interaction information stored in the Mylyn data. Mylyn is an Eclipse plug-in, which captures developers' interactions such as file editing and selection events with time spent. To evaluate the performance of MIMs in defect prediction, we build defect prediction (classification and regression) models using MIMs, traditional metrics, and their combinations. Our experimental results show that MIMs significantly improve defect classification and regression accuracy.

Background Virtually, all organisms on Earth have their own circadian rhythm, and humans are no exception. Circadian rhythms are associated with various human states, especially mood disorders, and disturbance of the circadian rhythm is known to be very closely related. Attempts have also been made to derive clinical implications associated with mood disorders using the vast amounts of digital log that is acquired by digital technologies develop and using computational analysis techniques. Objective This study was conducted to evaluate the mood state or episode, activity, sleep, light exposure, and heart rate during a period of about 2 years by acquiring various digital log data through wearable devices and smartphone apps as well as conventional clinical assessments. We investigated a mood prediction algorithm developed with machine learning using passive data phenotypes based on circadian rhythms. Methods We performed a prospective observational cohort study on 55 patients with mood disorders (major depressive disorder [MDD] and bipolar disorder type 1 [BD I] and 2 [BD II]) for 2 years. A smartphone app for self-recording daily mood scores and detecting light exposure (using the installed sensor) were provided. From daily worn activity trackers, digital log data of activity, sleep, and heart rate were collected. Passive digital phenotypes were processed into 130 features based on circadian rhythms, and a mood prediction algorithm was developed by random forest. Results The mood state prediction accuracies for the next 3 days in all patients, MDD …

The authors extend the integral manifold approach for the control of flexible joint robot manipulators from the known parameter case to the adaptive case. The resulting adaptive law, referred to as the corrective control law, consists of a fast component to damp the fast dynamics and a slow component which is designed based on the integral manifold theory and which consists of a rigid based component along with additional corrective terms. The authors give a detailed derivation of the corrective control law and present tracking results. They illustrate the implementation of the control law using simulation examples and study tracking performance and robustness with respect to an allowable range of stiffness and high adaptation gains.<>

Cognitive radio is an opportunistic communication technology designed to help unlicensed users utilize the maximum available licensed bandwidth. Cognitive radio has recently attracted a lot of research interest. However, little research has been done regarding security in cognitive radio, while much more research has been done on spectrum sensing and allocation problems. A selfish cognitive radio node can occupy all or part of the resources of multiple channels, prohibiting other cognitive radio nodes from accessing these resources. Selfish cognitive radio attacks are a serious security problem because they significantly degrade the performance of a cognitive radio network. In this article we identify a new selfish attack type in cognitive radio ad-hoc networks and propose an easy and efficient selfish cognitive radio attack detection technique, called COOPON, with multichannel resources by cooperative …

A massive amount of sensitive personal data is being collected and used by scientists, businesses, and governments. This has led to unprecedented threats to privacy rights and the security of personal data. There are few solutions that empower individuals to provide systematic consent agreements on distinct personal information and control who can collect, access, and use their data for specific purposes and periods. Individuals should be able to delegate consent rights, access consent-related information, and withdraw their given consent at any time. We propose a smart-contract-based dynamic consent management system, backed by blockchain technology, targeting personal data usage under the general data protection regulation. Our user-centric dynamic consent management system allows users to control their personal data collection and consent to its usage throughout the data lifecycle. Transaction history and logs are recorded in a blockchain that provides trusted tamper-proof data provenance, accountability, and traceability. A prototype of our system was designed and implemented to demonstrate its feasibility. The acceptability and reliability of the system were assessed by experimental testing and validation processes. We also analyzed the security and privacy of the system and evaluated its performance.

Describes the application of the WinWin paradigm to identify and resolve conflicts in a series of real-client, student-developer digital library projects. The paper is based on a case study of the statistical analysis of 15 projects and an in-depth analysis of one representative project. These analyses focus on the conflict resolution process, stakeholders' roles and their relationships to quality artifacts, and tool effectiveness. We show that stakeholders tend to accept satisfactory rather than optimal resolutions. Users and customers are more proactive in stating win conditions, whereas developers are more active in working toward resolutions. Further, we suggest that knowledge-based automated aids have potential to significantly enhance process effectiveness and efficiency. Finally, we conclude that such processes and tools have theoretical and practical implications in the quest for better software requirements elicitation.

To facilitate software quality assurance, defect prediction metrics, such as source code metrics, change churns, and the number of previous defects, have been actively studied. Despite the common understanding that developer behavioral interaction patterns can affect software quality, these widely used defect prediction metrics do not consider developer behavior. We therefore propose micro interaction metrics (MIMs), which are metrics that leverage developer interaction information. The developer interactions, such as file editing and browsing events in task sessions, are captured and stored as information by Mylyn, an Eclipse plug-in. Our experimental evaluation demonstrates that MIMs significantly improve overall defect prediction accuracy when combined with existing software measures, perform well in a cost-effective manner, and provide intuitive feedback that enables developers to recognize their own …

Uncertainty of system properties (eg, performance, reliability, security, interoperability, usability, etc.) often hinders the progress of requirements negotiation. Software architecture evaluation techniques enable stakeholders to clarify the uncertainty of system properties. In another hand, software architecture alternatives cannot be evaluated in a thorough way without consideration of different stakeholders’ negotiated requirements. Effective requirements negotiation is therefore needed to evaluate architecture alternatives.

Existing SPL cost estimation models [5–9] do not significantly consider the software quality cost, which is spent on removing undetected defects after product release. In general, the future costs for correction of defects undetected at product release consume a large portion of total maintenance costs. The proposed model is recommended, which includes the software quality cost in the SPL business case analysis. qCOPLIMO consists of the following two cost models: Relative Cost of Writing for Reuse (RCWR) for initial product line development and Relative Cost for Reuse (RCR) for the following product development cases.

The integration of Wireless Body Area Networks with a cloud computing platform creates a new digital ecosystem with advanced features called Cloud-assisted Wireless Body Area Networks. This ecosystem enables users to globally access e-healthcare services at competitive costs. However, the secure data communications between the cloud and Wireless Body Area Networks are critical because the data is related to users’ privacy information. In this paper, we propose the Multi-valued and Ambiguous Scheme to capture data confidentiality in the Cloud-assisted Wireless Body Area Networks since it is the most important issue. The approach combining the scheme with existing encryption schemes provides a general paradigm for deploying applications. The obtained results show that secure data communications between the cloud and Wireless Body Area Networks can be achieved.

Proof-of-authority (PoA) has become a popular consensus algorithm for permissioned blockchains, in which a group of trusted entities governs the networks. This algorithm provides fast consensus while requiring less computational resources and energy. Aura and Clique are two major implementations of PoA, which have their own set of advantages and disadvantages. In this paper, we evaluate the performance of both algorithms in terms of consistency, availability, partition tolerance, security, block time, and transaction throughput. The algorithms were implemented in Python, and experiments were conducted by connecting six consensus nodes having different computing power. The experimental results were comprehensively analyzed. It was observed that Clique provides higher availability and transaction throughput but lower security and consistency than Aura. The blockchains in the Aura network are …

Information security is a crucial technique for an organization to survive in these days. However, there is no integrated model to assess the security risk quantitatively and optimize its resources to protect organization information and assets effectively. In this paper, an integrated, quantitative risk analysis model is proposed including asset, threat and vulnerability evaluations by adapting software risk management techniques. It is expected to analyze security risk effectively and optimize resources to mitigate the risk.

During software programming, code readability is very important because it affects the understanding of the code context, facilitates communication and collaboration between team members, and it avoids problematic software maintenance. In this study, our research hypothesis was that the coding style affects the code readability. Developers who do not comply with coding conventions and guidelines may be more likely to produce code with a low level of readability. To test this hypothesis, we investigated coding rule violations in the source code files of five open source projects and correlated the observed violations with the scores rated by a readability estimation function. We tested whether significant violations of coding conventions affected the readability of developed codes and identified the violations that were related specifically to low readability quality. We consider that our findings will improve the …

Usability is one of the critical success factors for mobile applications. However, usability is not easy to improve. Many usability testing studies have been conducted to detect usability problems easily, however they usually carry a substantial cost and require specific expertise. In this paper, we present methods and tools to detect usability problems effectively via usability testing in mobile application. We expect users to interact with mobile applications in dissimilar ways when encountering usability problems. Based on this approach, we propose tracing, modeling and comparing methods for measuring the similarity of user behaviors. We evaluate the similarity of user behavior and use it in detecting problems. In addition, we developed tools for our methods to run in automatic way to save usability testing costs. An experiment was conducted using two mobile applications to confirm that our proposed method is useful …

Value-innovative requirements engineering guides software development organizations in creating new markets based on new product values for potential customers. Most requirements-engineering techniques and practices focus on eliciting requirements from existing, known customers. However, these techniques and practices aren't sufficient for surviving in current highly competitive markets. In particular, small organizations typically lack sufficient resources to compete effectively with large companies. W. Chan Kim and Renee Mauborgne proposed the blue-ocean strategy to create new marketplace value and so make competition irrelevant. A "blue ocean" is a potential market where competition doesn't yet exist.

Integrating blockchain technology with the Internet of Things (IoT) facilitates seamless interaction between IoT devices and systems to securely share, access, and exchange data. However, ensuring adequate access control within blockchain-enabled IoT (BIoT) systems remains a significant challenge. It is often difficult to adapt existing access control mechanisms to the dynamic and context-dependent nature of IoT environments, necessitating a robust context-aware approach to ensure adequate security and the privacy of resources within BIoT systems. In this article, we propose a novel smart contract-enabled context-aware access control (SC-CAAC) scheme for BIoT systems. It utilizes context-aware access control models that consider contextual information, including user profile, purpose, date, time, location, resource, and operating environment specifications, to make access control decisions. Smart contracts …

Ubicomp applications are characterized as situation-aware, frequently-and-ephemerally-communicated and QoS-properties-associated. Using middleware to provide multiple QoS support for these ubicomp applications will enhance the development of the ubicomp applications. To satisfy the different QoS requirements of various applications in ubicomp environments, which are heterogeneous and resource-variant, it is important for the underlining middleware to adapt to different QoS requirements and environments. Situation-Aware Contract Specification Language (SA-CSL) specifies the QoS requirements of the applications. The specification includes requirements in situation-awareness, real-time constraints and security properties. This specification is used to customize the middleware architecture to better satisfy these requirements. SA-CSL is based on the Separation of Concern (SoC) discipline used in the …

One of the biggest risks in software requirements engineering is the risk of overemphasizing one quality attribute requirement (eg, performance) at the expense of others at least as important (eg, evolvability and portability). This paper describes an exploratory knowledge-based tool for identifying potential conflicts among quality attributes early in the software/system life cycle. The Quality Attribute Risk and Conflict Consultant (QARCC) examines the quality attribute tradeoffs involved in software architecture and process strategies (eg, one can improve portability via a layered architecture, but usually at some cost in performance). It operates in the context of the USC-CSE WinWin system, a groupware support system for determining software and system requirements as negotiated win conditions.

In recent times, electronic portfolios (e-portfolios) are being increasingly used by students and lifelong learners as digital online multimedia résumés that showcase their skill sets and achievements. E-portfolios require secure, reliable, and privacy-preserving credential issuance and verification mechanisms to prove learning achievements. However, existing systems provide private institution-wide centralized solutions that primarily rely on trusted third parties to issue and verify credentials. Furthermore, they do not enable learners to own, control, and share their e-portfolio information across organizations, which increases the risk of forged and fraudulent credentials. Therefore, we propose a consortium blockchain-based e-portfolio management scheme that is decentralized, secure, and trustworthy. Smart contracts are leveraged to enable learners to completely own, publish, and manage their e-portfolios, and also enable potential employers to verify e-portfolio credentials and artifacts without relying on trusted third parties. Blockchain is used as an immutable distributed ledger that records all transactions and logs for tamper-proof trusted data provenance, accountability, and traceability. This system guarantees the authenticity and integrity of user credentials and e-portfolio data. Decentralized identifiers and verifiable credentials are used for user profile identification, authentication, and authorization, whereas verifiable claims are used for e-portfolio credential proof authentication and verification. We have designed and implemented a prototype of the proposed scheme using a Quorum consortium blockchain network. Based on the evaluations …

Professor/Head Director

Mpyana Mwamba Merlec, Ph.D.

Nday Kabulo Sinai

Seungkwon Lee

The rapid adoption of Verifiable Credentials (VCs) has intensified privacy and security challenges in digital verification, as traditional systems often require full credential disclosure, creating privacy risks and expanding the attack surface. Ensuring end-to-end privacy, security, and verifiability in such systems remains a significant challenge. This paper introduces ZK-Sandbox , a Zero-Knowledge Data Sandbox System that integrates zero-knowledge proofs (ZKPs), decentralized identifiers (DIDs), and blockchain anchoring to enable credential validation and verifiable badge issuance without exposing underlying data. ZK-Sandbox supports complex predicate evaluation by securely aggregating multiple VCs from trusted issuers, processing them via JSON Web Token signature verification, Circom-based zk-SNARK circuits, and Docker-isolated execution. The system issues VC-compatible ZK-Badges, cryptographically …

Intelligent Blockchain Engineering Laboratory

교수님 소개

인호 (Peter)

연구실 소개

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

ZK-Sandbox: Zero-Knowledge Data Sandbox System for Enhancing End-to-End Security and Privacy of Verifiable Credentials

GNNRec: A Graph-Based Neural Network Model for Efficient and Robust Product Recommendation

PALC: Preference Alignment via Logit Calibration

연구실 보유 특허

대학별 입시끈

우리 연구실 모집

교수님 소개

인호 (Peter)

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

ZK-Sandbox: Zero-Knowledge Data Sandbox System for Enhancing End-to-End Security and Privacy of Verifiable Credentials

GNNRec: A Graph-Based Neural Network Model for Efficient and Robust Product Recommendation

PALC: Preference Alignment via Logit Calibration

연구실 보유 특허

최근 3년간 연구실적 높은 연구실

대학별 입시끈

우리 연구실 모집