• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.05a
• /
• pp.264-267
• /
• 2022

Recently, federated learning (FL) has increased prominence as a viable approach for enhancing user privacy and data security by allowing collaborative multi-party model learning without exchanging sensitive data. Despite this, most present FL systems still depend on a centralized aggregator to generate a global model by gathering all submitted models from users, which could expose user privacy and the risk of various threats from malicious users. To solve these issues, we suggested a safe FL framework that employs differential privacy to counter membership inference attacks during the collaborative FL model training process and empowers blockchain to replace the centralized aggregator server.

• Journal of Korea Game Society
• /
• v.9 no.5
• /
• pp.53-61
• /
• 2009

Game industry, especially MMORPG (Massively Multiplayer Online Role Playing Game) has rapidly been expanding in these days. In this background, lots of online game security incidents have been increasing and getting more diversity. One of the most critical security incidents is 'Bots', mimics human player's playing behaviors. Bots performs the task without any manual works, it is considered unfair with other players. So most game companies try to block Bots by analyzing the packets between clients and servers. However this method can be easily attacked, because the packets are changeable when it is send to server. In this paper, we propose a Bots detection method by observing the playing patterns of game characters with data on server. In this method, Bots developers cannot handle the data, because it is working on server. Therefore Bots cannot avoid it and we can find Bots users more completely.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.7
• /
• pp.861-868
• /
• 2019

Various server-based services such as big data, IoT and artificial intelligence have been made online. As a result, the demand for IDC to support stable server operation is increasing. IDC is a server-based facility with a stable line and power supply facility that manages 20 to 30 servers in an efficiently separated rack-level subnetwork. Here, we need a way to efficiently manage servers security, firewall, and traffic on a rack-by-rack basis. Including traffic shaping capabilities that control routers, firewalls, IPS, and line speeds, as well as VPN technology, a recent interest. If three or five kinds of commercial equipment are adopted to support this, it may be a great burden to the management cost as well as the introduction cost. Therefore, in this paper, we propose a method to implement the five functions in one rack-unit small integrated security router. In particular, IDC intends to integrate traffic shaping and IPS, which are essential technologies, and to propose the utility accordingly.

• International journal of advanced smart convergence
• /
• v.8 no.3
• /
• pp.69-77
• /
• 2019

Today, most of elevators have an emergency call facility for emergency situations. However, if the network installed in the elevator is also out of power, it cannot be used for the elevator remote monitoring and management. So, we develop an integrated and unified emergency call system, which can transmit not only telephone call but also data signals using PSTN(Public Switched Telephone Network) in order to remote monitoring and management of elevators, even though a power outage occurs. The proposed integrated emergency call system to process multiple data such as voice and operational information is a multi-channel board system which is composed of an emergency phone signal processing module and an operational information processing module in the control box of elevator. In addition, the RMS(remote management server) systems based on the Web consist of a dial-up server and a remote monitoring server where manages the elevator's operating information, status records, and operational faults received via the proposed integrated and unified emergency call system in real time. So even if there's a catastrophic emergency, the proposed RMS systems shall ensure and maintain the safety of passengers inside the elevator. Also, remote control of the elevator by this system should be more efficient and secure. In near future, all elevator emergency call system need to support multifunctional capabilities to transmit operational data as well as phone calls for the safety of passengers. In addition, for safer elevators, it is necessary to improve them more efficiently by combining them with high-tech technologies such as the Internet of Things and artificial intelligence.

• Journal of Internet Computing and Services
• /
• v.23 no.4
• /
• pp.87-94
• /
• 2022

Recently, with the development of information and communication infrastructure, the number of Internet access devices is rapidly increasing. Smartphones, laptops, computers, and even IoT devices are receiving information and communication services through Internet access. Since most of the device operating environment consists of web (WEB), it is vulnerable to web cyber attacks using web shells. When the web shell is uploaded to the web server, it is confirmed that the attack frequency is high because the control of the web server can be easily performed. As the damage caused by the web shell occurs a lot, each company is responding to attacks with various security devices such as intrusion prevention systems, firewalls, and web firewalls. In this case, it is difficult to detect, and in order to prevent and cope with web shell attacks due to these characteristics, it is difficult to respond only with the existing system and security software. Therefore, it is an automated defense system through the collection and analysis of web shells based on artificial intelligence machine learning that can cope with new cyber attacks such as detecting unknown web shells in advance by using artificial intelligence machine learning and deep learning techniques in existing security software. We would like to propose about. The machine learning-based web shell defense system model proposed in this paper quickly collects, analyzes, and detects malicious web shells, one of the cyberattacks on the web environment. I think it will be very helpful in designing and building a security system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.165-167
• /
• 2022

The proportion of cat cats among companion animals has been increasing at an average annual rate of 25.4% since 2012. Cats have strong wildness compared to dogs, so they have a characteristic of hiding diseases well. Therefore, when the guardian finds out that the cat has a disease, the disease may have already worsened. Symptoms such as anorexia (eating avoidance), vomiting, diarrhea, polydipsia, and polyuria in cats are some of the symptoms that appear in cat diseases such as diabetes, hyperthyroidism, renal failure, and panleukopenia. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia (drinking a lot of water), polyuria (a large amount of urine), and frequent urination (urinating frequently) more quickly. In this paper, 1) Efficient version of DeepLabCut for posture prediction running on an artificial intelligence server, 2) yolov4 for object detection, and 3) LSTM are used for behavior prediction. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the main server system.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.4
• /
• pp.99-105
• /
• 2023

In this paper, an intelligent CCTV was designed and experimentally developed by using an IOT device, Raspberry Pi, and artificial intelligence technology. Object Detection technology was used to detect the number of people on the CCTV screen, and Action Detection technology provided by OpenPose was used to detect emergency situations. The proposed system has a structure of CCTV, server and client. CCTV uses Raspberry Pi and USB camera, server uses Linux, and client uses iPhone. Communication between each subsystem was implemented using the MQTT protocol. The system developed as a prototype could transmit images at 2.7 frames per second and detect emergencies from images at 0.2 frames per second.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.2
• /
• pp.76-90
• /
• 2024

Although artificial intelligence (AI) can be utilized in various domains such as smart city, healthcare, it is limited due to concerns about the exposure of personal and sensitive information. In response, the concept of distributed machine learning has emerged, wherein learning occurs locally before training a global model, mitigating the concentration of data on a central server. However, overall learning phase in a collaborative way among multiple participants poses threats to data privacy. In this paper, we systematically analyzes recent trends in privacy protection within the realm of distributed machine learning, considering factors such as the presence of a central server, distribution environment of the training datasets, and performance variations among participants. In particular, we focus on key distributed machine learning techniques, including horizontal federated learning, vertical federated learning, and swarm learning. We examine privacy protection mechanisms within these techniques and explores potential directions for future research.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.7
• /
• pp.149-158
• /
• 2024

This study aims to design and develop AirDeep-Room, a multi-sensor system for monitoring air quality in various indoor environments. The system measures CO2, TVOC, particulate matter, temperature, and humidity in real-time. By integrating multiple sensors, AirDeep-Room allows convenient correlation analysis using low data format in real-time. The sensor system was installed in a server room and a classroom. Data analysis showed a negative correlation of -0.24 between temperature and humidity in the server room, and a positive correlation of 0.43 in the classroom, indicating different interactions. A high correlation (r=0.69) between the number of students and concentrations of CO2 and TVOC demonstrated the significant impact of occupancy on air quality. AirDeep-Room effectively manages air quality across various environments and provides essential data for improving air quality in densely populated areas.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.879-884
• /
• 2004

This paper describes the development of a synthetic multi-agent called KMITL Cadence 2003. KMITL Cadence 2003 is a robotic soccer simulation team consisting of eleven autonomous software agents. Each agent operates in a physical soccer simulation model called Robocup Soccer Server which provides fully distributed and real-time multi-agent system environment. All teammates have to cooperate to achieve the common goal of winning the game. The simulation models many aspects of the football field such as noise in ball movements, noisy sensors, unreliable communication channel between teammates and actuators, limited physical abilities and restricted communication. This paper addresses the algorithm to develop the soccer agents to perform basic actions which are scoring, passing ball and blocking the opponents effectively. The result of this development is satisfactory because the successful scoring attempts is increased from 11.1% to 33.3%, successful passing ball attempts is increased from 22.08% to 63.64%, and also, successful intercepting attempts is increased from 88% to 97.73%.