• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.140-142
• /
• 2023

Federated learning (FL) is a new paradigm in machine learning (ML) that enables multiple devices to collaboratively train a shared ML model without sharing their local data. FL is well-suited for applications where data is sensitive or difficult to transmit in large volumes, or where collaborative learning is required. The Internet of Underwater Things (IoUT) is a network of underwater devices that collect and exchange data. This data can be used for a variety of applications, such as monitoring water quality, detecting marine life, and tracking underwater vehicles. However, the harsh underwater environment makes it difficult to collect and transmit data in large volumes. FL can address these challenges by enabling devices to train a shared ML model without having to transmit their data to a central server. This can help to protect the privacy of the data and improve the efficiency of training. In this view, this paper provides a brief overview of Fed-IoUT, highlighting its various applications, challenges, and opportunities.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.4
• /
• pp.811-817
• /
• 2009

The rapid growth of network based IT systems has resulted in continuous research of security issues. Probe intrusion detection is an area of increasing concerns in the internet community. Recently, a number of probe intrusion detection schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of probe intrusion. They can not detect new patterns of probe intrusion. Therefore, it is necessary to develop a new Probe Intrusion Detection technology that can find new patterns of probe intrusion. In this paper, we proposed a new network based probe intrusion detector(NePID) using anomaly traffic analysis and fuzzy cognitive maps that can detect intrusion by the denial of services attack detection method utilizing the packet analyses. The probe intrusion detection using fuzzy cognitive maps capture and analyze the packet information to detect syn flooding attack. Using the result of the analysis of decision module, which adopts the fuzzy cognitive maps, the decision module measures the degree of risk of denial of service attack and trains the response module to deal with attacks. For the performance evaluation, the "IDS Evaluation Data Set" created by MIT was used. From the simulation we obtained the max-average true positive rate of 97.094% and the max-average false negative rate of 2.936%. The true positive error rate of the NePID is similar to that of Bernhard's true positive error rate.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.46 no.8
• /
• pp.22-33
• /
• 2009

Mobile Ad Hoc Networks (MANETs) are self-organized networks that do not rely in their operation on wired infrastructure. As in any networking technology, security is an essential element in MANET as well, for proliferation of this type of networks. But supporting secure communication in MANETs proved to be a significant challenge, mainly due to the fact that the set of nodes in the network can change frequently and rapidly and due to the lack of access to the wired infrastructure. In particular, the trust model and the authentication protocols, which were developed for wired and infrastructure-based networks, cannot be used in MANETs. In [1], we addressed the problem of efficient authentication of distributed mobile users in geographically large networks and proposed a new authentication scheme for this case of MANETs. The proposed scheme exploits randomized groups to efficiently share authentication information among nodes that together implement the function of a distributive Certification Authority(CA). In this paper, we analyze numerically the performance of authentication method using randomized groups and compare with the simulation result.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.2
• /
• pp.689-700
• /
• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.

• Journal of the Korea Convergence Society
• /
• v.9 no.8
• /
• pp.1-8
• /
• 2018

In the field of biometric security such as face and iris recognition, it is essential to extract facial features such as eyes and lips. In this paper, we have studied a method of detecting eye and lip region in face image using faster R-CNN. The faster R-CNN is an object detection method using deep running and is well known to have superior performance compared to the conventional feature-based method. In this paper, feature maps are extracted by applying convolution, linear rectification process, and max pooling process to facial images in order. The RPN(region proposal network) is learned using the feature map to detect the region proposal. Then, eye and lip detector are learned by using the region proposal and feature map. In order to examine the performance of the proposed method, we experimented with 800 face images of Korean men and women. We used 480 images for the learning phase and 320 images for the test one. Computer simulation showed that the average precision of eye and lip region detection for 50 epoch cases is 97.7% and 91.0%, respectively.

• Journal of Advanced Navigation Technology
• /
• v.12 no.1
• /
• pp.34-45
• /
• 2008

Broadcast encryption schemes are applied to transmit digital informations of multimedia, software, Pay-TV etc. in public network. User acquires message or session key to use key that broadcaster transmits, broadcaster need process that generation and distribution key in these process. Also, user secession new when join efficient key renewal need. In this paper, introduce about efficient key generation and distribution, key renewal method. The temporary conference environment base structure against an each mobile device wild gap. Without the transmission possible, it follows infrequent location change and with the quality where the key information change flow. Thus, in this paper, in order to apply to the embedded computing environment and the key generation and the efficient key renewal are done when the mobile device is used of the specify space it proposes.

• Journal of Korea Society of Industrial Information Systems
• /
• v.11 no.1
• /
• pp.29-37
• /
• 2006

Due to the spread of mobile communication with the development of computer network, nowadays various types of multimedia data play an important role in many areas such as entertainments, culture contents, e-commerce or medical science. But for the real application of these data, the security in the course of saving or transferring them through the public network should be assured. In this sense, many encryption algorithm have been developed and utilized. Nonetheless, most of them have focused on the text data. So they may not be suitable to the multimedia application because of their large size and real time constraint. In this paper, a chaotic map has been employed to create a symmetric stream type of encryption scheme which may be applied to the digital images with a large amounts of data. Then an efficient algebraic encryption algorithm based on the elementary operations of the Boolean matrix and image data characteristics.

• Journal of the Semiconductor & Display Technology
• /
• v.18 no.3
• /
• pp.122-126
• /
• 2019

These-days technology related to IoT (Internet of Thing) is widely used and there are many types of smart system based IoT like smart health, smart building and so on. In smart health system, it is possible to check someone's health by analyzing data from wearable IoT device like smart watch. Smart building system aims to collect data from sensor such as humidity, temperature, human counter like that and control the building for energy efficiency, security, safety and so forth. Furthermore, smart city system can comprise several smart systems like smart building, smart health, smart mobility, smart energy and etc. In this paper, we propose multimedia IoT based intelligent emergency alarm system for smart city. In existing IoT based smart system, it communicates lightweight data like text data. In the past, due to network's limitations lightweight IoT protocol was proposed for communicating data between things but now network technology develops, problem which is to communicate heavy data is solving. The proposed system obtains video from IP cameras/CCTVs, analyses the video by exploiting AI algorithm for detecting emergencies and prevents them which cause damage or death. If emergency is detected, the proposed system sends warning message that emergency may occur to people or agencies. We built prototype of the intelligent emergency alarm system based on MQTT and assured that the system detected dangerous situation and sent alarm messages. From the test results, it is expected that the system can prevent damages of people, nature and save human life from emergency.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.11
• /
• pp.7541-7548
• /
• 2015

Wireless Sensor Networks is the technology which is used in explore role for military purposes, as well as various fields such as industrial equipment management, process management, and leverage available technologies by distributing node into various areas. but there are some limitations about energy, processing power, and memory storage capacity in wireless sensor networks environment, because of tiny hardware, so various routing protocols are proposed to overcome it. however existing routing protocols are very vulnerable in the intercommunication, because they focus on energy efficiency, and they can't use existing encryption for it, Because of sensor's limitations such like processing power and memory. Therefore, this paper propose mutual authentication scheme that prevent various security threats by using mutual authentication techniques and, Key generation and updating system as taking into account energy efficiency.

• KIPS Transactions on Computer and Communication Systems
• /
• v.1 no.2
• /
• pp.109-118
• /
• 2012

As a result of the prevalence of smartphone, various mobile services became faster by LTE networks. Because many mobile devices are used more wireless services, heavy signaling traffic for authentication could be generated. Authentication is an important factor in wireless networks to identify devices; it is the start of wireless networks. This paper analyzes previous patterns for more effective authentication in accessing of another external networks. We propose a fast authentication scheme for minimizing of signaling cost between the authentication server and external networks. And we calculate the rate of authentication occurrence in LTE networks using mathematical modeling as well as the change of signaling cost for authentication in various network environments. Finally, we calculate the optimized number of authentication data and show the effectiveness for authentication signaling costs.