• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.1019-1034
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• 2022

Malware attacks become more prevalent in the hyper-connected society of the 4th industrial revolution. To respond to such malware, automation of malware detection using artificial intelligence technology is attracting attention as a new alternative. However, using artificial intelligence without collateral for its reliability poses greater risks and side effects. The EU and the United States are seeking ways to secure the reliability of artificial intelligence, and the government announced a reliable strategy for realizing artificial intelligence in 2021. The government's AI reliability has five attributes: Safety, Explainability, Transparency, Robustness and Fairness. We develop four elements of safety, explainable, transparent, and fairness, excluding robustness in the malware detection model. In particular, we demonstrated stable generalization performance, which is model accuracy, through the verification of external agencies, and developed focusing on explainability including transparency. The artificial intelligence model, of which learning is determined by changing data, requires life cycle management. As a result, demand for the MLops framework is increasing, which integrates data, model development, and service operations. EXE-executable malware and documented malware response services become data collector as well as service operation at the same time, and connect with data pipelines which obtain information for labeling and purification through external APIs. We have facilitated other security service associations or infrastructure scaling using cloud SaaS and standard APIs.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.134-141
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• 2003

A major research issue associated with service robots is the creation of an environment recognition system for mobile robot navigation that is robust and efficient on various environment situations. In recent years, intelligent autonomous mobile robots have received much attention as the types of service robots for serving people and industrial robots for replacing human. To help people, robots must be able to sense and recognize three dimensional space where they live or work. In this paper, we propose a three dimensional environmental modeling method based on an edge enhancement technique using a planar fitting method and a neural network technique called "Growing Neural Gas Network." Input data pre-processing provides probabilistic density to the input data of the neural network, and the neural network generates a graphical structure that reflects the topology of the input space. Using these methods, robot's surroundings are autonomously clustered into isolated objects and modeled as polygon patches with the user-selected resolution. Through a series of simulations and experiments, the proposed method is tested to recognize the environments surrounding the robot. From the experimental results, the usefulness and robustness of the proposed method are investigated and discussed in detail.in detail.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.314-317
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• 2004

With the advance of network and software infrastructure, Grid-computing technology on a cluster of heterogeneous computing resources becomes pervasive. Grid computing is required a coordinated use of an assembly of distributed computers, which are linked by WAN. As the number of grid system components increases, the probability of failure in the grid computing is higher than that in a traditional parallel computing. To provide the robustness of grid applications, fault detection is critical and is essential elements in design and implementation. In this paper, a OGSA based process fault-detection services presented to provide high reliability under low network traffic environment.

• Journal of Digital Contents Society
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• v.15 no.3
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• pp.357-363
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• 2014

In this paper, we propose a new audio forensic marking system for protecting the copyright of the Internet-based music streaming services. In the proposed method, in order to guarantee the QoS of the streaming service, high speed, and generates a forensic mark inserted MP3 file. We make pre-marking process and generate a new forensic marked MP3 file, a combination of the pre-marked MP3 frame, the inserted user information. Experimental results show that the proposed method satisfactory results robustness and imperceptibility, and real-time properties. In addition, we were confirmed that the real-time embedding and detection from the streaming-based audio forensic marking system that has been implemented on the server/client is possible.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.1-11
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• 2024

Payment systems are evolving, and this study examines how blockchain and AI improve online transactional security and service quality. The study examines micro and macro payment systems, compares online, and offline methods all over the world. The study also examines how blockchain and AI affect payment system security, privacy, and efficiency globally and rapidly digitizing economy. Digital payment methods are growing all over the world with high literacy and digital engagement, but they face challenges. The research highlights cybersecurity threats and the need to balance user convenience and security. It suggests blockchain and AI improve online payment services, supporting the policies for different countries. In this extensive research survey, we compare and evaluate the strengths and weaknesses of various payment systems, their practicality, and their robustness. This study also examines how technological innovations and payment systems interact to reveal how blockchain and AI could transform the financial sector. It seeks to understand how technology-enhancing service quality can boost customer satisfaction and financial stability in the digital age. The findings should help policymakers, financial institutions, and technology developers optimize online payment systems for a more secure and efficient digital economy.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.203-214
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• 2024

This study seeks to provide implications for domestic-related policies through exploratory analysis research to support AI-based policy decision-making. The following should be considered when establishing an AI-based decision-making model in Korea. First, we need to understand the impact that the use of AI will have on policy and the service sector. The positive and negative impacts of AI use need to be better understood, guided by a public value perspective, and take into account the existence of different levels of governance and interests across public policy and service sectors. Second, reliability is essential for implementing innovative AI systems. In most organizations today, comprehensive AI model frameworks to enable and operationalize trust, accountability, and transparency are often insufficient or absent, with limited access to effective guidance, key practices, or government regulations. Third, the AI system is accountable. The OECD AI Principles set out five value-based principles for responsible management of trustworthy AI: inclusive growth, sustainable development and wellbeing, human-centered values and fairness values and fairness, transparency and explainability, robustness, security and safety, and accountability. Based on this, we need to build an AI-based decision-making system in Korea, and efforts should be made to build a system that can support policies by reflecting this. The limiting factor of this study is that it is an exploratory study of existing research data, and we would like to suggest future research plans by collecting opinions from experts in related fields. The expected effect of this study is analytical research on artificial intelligence-based decision-making systems, which will contribute to policy establishment and research in related fields.

• The Journal of Society for e-Business Studies
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• v.7 no.1
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• pp.19-34
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• 2002

The main objective of this research is to find out whether there exist any user interface factors that influence service information management professionals(SIMP)'s business activities on the web. The result of this study shows that there exists a significant level of difference between two groups of office Professionals： SIMP and general office management professionals on user interface factors. We analyzed the past and current research results and focused on four major evaluation categories： (1) web design, (2) structure, (3) navigation, and (4) interaction and identified 26 evaluation items in those categories. The study has been initiated by an intuition that there might be a significant difference in sets of user interface factors that influence SIMP and general office professionals. From the list of Best 100 Web Sites the best 30 information-providing web sites and the best 30 service-providing web sites were carefully chosen by a panel of 10 members for each group. To evaluate 60 web sites, another panel was formed by 30 professionals from each group, and they conducted evaluation in their own work settings. Reliability analysis on user interface factors and T-test to find out any influencing factors on SIMP were performed. As a result of this study, we have recognized that clarity, formation, consciseness, economics, and robustness are the most influencing user interface factors for web designers to concern when they develop web sites for SIMP. The study result can be improved by enhancing reliability of choosing target web sites In investigate and panel members. Also, in the future study it is recommended to investigate influencing factors for office professionals in terms of. age, sex, experience, academic background, etc.

• The KIPS Transactions:PartC
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• v.12C no.6 s.102
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• pp.891-900
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• 2005

This paper studies network recovery methods for WDM optical mesh networks, concentrating on improving spare resource utilization. The resource efficiency can be obtained by sharing spare resources needed for network recovery. To improve the sharability of spare resources in WDM networks, methods to share backup paths us well as spare capacity should be studied. The proposed method in this paper uses multiple ring-covers and this method provides fast and simple recovery operation by exploiting the characteristics of logical ring topology, and also provides efficient resource utilization by using multiple distributed backup paths to improve the sharability of overall spare resources in the networks. This method can provide layered reliability to network service by enabling hierarchical robustness against multiple failures. The performance results show that the proposed method provide improved resource efficiency for single failure and enhanced robustness for multiple failures.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.241-253
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• 2008

UCC(User Created Content) has brought about much change in the way Internet users produce, publish, and share digital content. That means that Internet users are participating in the UCC service much mure voluntarily, and interacting each other mure proactively to meet their social-psychological needs such as self-expression, social presence and so on. Also, there has been the sharp increase in variety and volume of digital content on Internet. The reasons why are that UCC enables Internet users to produce and publish their own content with much low cost, and lowers the entrance barriers to the digital content market. Like this, UCC causes the unbundling of the value chain of digital content, resulting in the high uncertainty and complexity, and then leading to the low healthiness of UCC value chain in terms of productivity, robustness, niche creation, and safety. Thus, this paper is to identify the status and problems of UCC value chain and present the way how to enhance the healthiness of UCC value chain more comprehensively and systematically.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.197-209
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• 2011

This paper presents a localization system using ceiling images in a large indoor environment. For a system with low cost and complexity, we propose a single camera based system that utilizes ceiling images acquired from a camera installed to point upwards. For reliable operation, we propose a method using hybrid features which include natural landmarks in a natural scene and artificial landmarks observable in an infrared ray domain. Compared with previous works utilizing only infrared based features, our method reduces the required number of artificial features as we exploit both natural and artificial features. In addition, compared with previous works using only natural scene, our method has an advantage in the convergence speed and robustness as an observation of an artificial feature provides a crucial clue for robot pose estimation. In an experiment with challenging situations in a real environment, our method was performed impressively in terms of the robustness and accuracy. To our knowledge, our method is the first ceiling vision based localization method using features from both visible and infrared rays domains. Our system can be easily utilized with a variety of service robot applications in a large indoor environment.