• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.639-641
• /
• 2022

With the increasing of aging population, a lot of researches on monitoring systems for solitary senior citizens are under study. In general, a monitoring system provides a monitoring service by computing the information of vision, sensors, and measurement values on a server. Design considering data security is essential because a risk of data leakage exists in the structure of the system employing the server. In this paper, we propose a intelligent monitoring system for solitary senior citizens with vision-based security architecture. The proposed system protects privacy by ensuring high security through an architecture that blocks communication between a camera module and a server by employing an edge AI module. The edge AI module was designed with Verilog HDL and verified by implementing on a Field Programmable Gate Array (FPGA). We tested our proposed system on 5,144 frame data and demonstrated that a dangerous detection signal is generated correctly when human motion is not detected for a certain period.

• International Journal of Computer Science & Network Security
• /
• v.22 no.11
• /
• pp.357-366
• /
• 2022

Artificial intelligence (AI) is the replication of human intelligence by computer systems and machines using tools like machine learning, deep learning, expert systems, and natural language processing. AI can be applied in administrative settings to automate repetitive processes, analyze and forecast data, foster social communication skills among staff, reduce costs, and boost overall operational effectiveness. In order to understand how AI is being used for administrative duties in various organizations, this paper gives a critical dialogue on the topic and proposed a framework for using artificial intelligence in organizations. Additionally, it offers a list of specifications, attributes, and requirements that organizations planning to use AI should consider.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2024.05a
• /
• pp.371-373
• /
• 2024

디지털 헬스케어 기술이 고도화되면서 디지털 치료제와 원격 의료 서비스가 의료 산업과 일상생활에 널리 활용되고 있다. 그러나 빅데이터 기반의 AI 서비스가 보편화될 수 있도록 데이터 수집, 가공, 활용 과정에서 개인정보가 남용되거나 유출되는 보안 위협도 증가하고 있다. 본 논문에서는 AI 챗봇을 활용한 정신건강 서비스를 위한 보안 위협 대응책을 마련하고 개인정보보호 가이드라인을 수립하여 사용자들에게 안전한 서비스를 제공하고 개인정보보호를 강화하는 AI 챗봇 서비스를 위한 데이터 보안 가이드라인을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2024.05a
• /
• pp.45-46
• /
• 2024

스프링 부트는 개발 및 실행 환경 설정이 간편하기 때문에 백엔드 개발에 활용되는 프레임워크이고 React는 프론트엔드 개발에 활용되는 프레임워크이다. 본 논문에서는 스프링 부트와 React를 사용하는 웹 응용에서 로그인 시스템 구축 시 JWT를 활용하는 방법과 구조에 관해 설명하였다.

• Journal of Internet Computing and Services
• /
• v.23 no.6
• /
• pp.97-105
• /
• 2022

This paper explains trends in security technologies for ICS. Since ICS is usually applied to large-scale national main infrastructures and industry fields, minor errors caused by cyberattack could generate enormous economic cost. ICS has different characteristic with commonly used IT systems, so considering security threats of ICS separately with IT is needed for developing modern security technology. This paper introduce framework for ICS that analyzes recent cyberattack tactics & techniques and find out trends in Intrusion Detection System (IDS) which is representative technology for ICS security, and analyzes AI technologies used for IDS. Specifically, this paper explains data collection and analysis for applying AI techniques, AI models, techniques for evaluating AI Model.

• International Journal of Computer Science & Network Security
• /
• v.24 no.1
• /
• pp.9-16
• /
• 2024

AI or Artificial Intelligence has been a significant tool used in the organisational backgrounds for an effective improvement in the management methods. The processing of the information and the analysis of the data for the further achievement of heightened efficiency can be performed by AI through its data analytics measures. In the medical field, AI has been integrated for an improvement within the management of the medical services and to note a rise in the levels of customer satisfaction. With the benefits of reasoning and problem solving, AI has been able to initiate a range of benefits for both the consumers and the medical personnel. The main benefits which have been noted in the integration of AI would be integrated into the study. The issues which are noted with the integrated AI usage for the medical sector would also be identified in the study. Medical Image Processing has been seen to integrate 3D image datasets with the medical industry, in terms of Computed Tomography (CT) or Magnetic Resonance Imaging (MRI). The usage of such medical devices have occurred in the diagnosis of the patients, the development of guidance towards medical intervention and an overall increase in the medical efficiency. The study would focus on such different tools, adhered with AI for increased medical improvement.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.32 no.5
• /
• pp.997-1008
• /
• 2022

Today, AI(Artificial Intelligence) technology is being extensively researched in various fields, including the field of malware detection. To introduce AI systems into roles that protect important decisions and resources, it must be a reliable AI model. AI model that dependent on training dataset should be verified to be robust against new attacks. Rather than generating new malware detection, attackers find malware detection that succeed in attacking by mass-producing strains of previously detected malware detection. Most of the attacks, such as adversarial attacks, that lead to misclassification of AI models, are made by slightly modifying past attacks. Robust models that can be defended against these variants is needed, and the Robustness level of the model cannot be evaluated with accuracy and recall, which are widely used as AI evaluation indicators. In this paper, we experiment a framework to evaluate robustness level by generating an adversarial sample based on one of the adversarial attacks, C&W attack, and to improve robustness level through adversarial training. Through experiments based on malware dataset in this study, the limitations and possibilities of the proposed method in the field of malware detection were confirmed.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.10
• /
• pp.1375-1380
• /
• 2021

Korea's security response to application service app is still insufficient due to the initial opening of the public safety network. Therefore, preemptive security measures are essential. In this study, we proposed to establish a 'public safety network app security system' to prevent potential vulnerabilities to the app store that distributes app in public safety network and android operating system that operate app on dedicated terminal devices. In order for an application service app to be listed on the public safety network mobile app store, a dataset of malicious and normal app is first established to extract characteristics and select the most effective AI model to perform static and dynamic analysis. According to the analysis results, 'Safety App Certificate' is certified for non-malicious app to secure reliability for listed apps. Ultimately, it minimizes the security blind spots of public safety network app. In addition, the safety of the network can be secured by supporting public safety application service of certified apps.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.655-656
• /
• 2021

April 2021, Disaster Safety Communication Network services have been launched, but security functions are weak at the beginning of the service. The current security method for Android-based APP is using Google Protect's technology to detect malware. Malware is difficult to detect directly because there are various types, so by applying malware detection technology that combines AI and Google Protect technology to Disaster Safety Communication Networks, research on how to implement 'AI-based Disaster Satety Communication Network Protect'.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.3
• /
• pp.549-559
• /
• 2023

As mobile edge computing (MEC) is gaining attention as a core technology of 5G networks, edge AI technology of 5G network environment based on mobile user data is recently being used in various fields. However, as in traditional AI security, there is a possibility of adversarial interference of standard 5G network functions within the core network responsible for edge AI core functions. In addition, research on data poisoning attacks that can occur in the MEC environment of standalone mode defined in 5G standards by 3GPP is currently insufficient compared to existing LTE networks. In this study, we explore the threat model for the MEC environment using NWDAF, a network function that is responsible for the core function of edge AI in 5G, and propose a feature selection method to improve the performance of detecting data poisoning attacks for Leaf NWDAF as some proof of concept. Through the proposed methodology, we achieved a maximum detection rate of 94.9% for Slowloris attack-based data poisoning attacks in NWDAF.