• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.131-145
• /
• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.10
• /
• pp.1958-1968
• /
• 2015

Things intelligence communication (M2M or IoT) service activation and global company of OneM2M-related business on aggressive investing and has led to the acceleration of change in the ICT market. But a variety of hacking security technology because of the possibility of secure communication (data exposure, theft, modification, deletion, etc.) has been issued as an important requirement. In this paper, we propose a mutual authentication protocol for secure communications chameleon hash based on the M2M environment. The results of performance analysis efficiency is encryption and decryption an average of 0.7%, calculated rate showed good results as compared to the target algorithm, equivalent to a 3%(Average 0.003 seconds) difference, mutual authentication and encryption region by using the key update advantage of ECC(Elliptic Curve Cryptography)based Chameleon hash function is signed of the operational efficiency, using a collision message verifiable properties demonstrated strong security of the communication section.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.6
• /
• pp.2148-2167
• /
• 2021

The proliferation of the Internet of Things (IoT) technologies and applications, especially the rapid rise in the use of mobile devices, from individuals to organizations, has led to the fundamental role of secure wireless networks in all aspects of services that presented with many opportunities and challenges. To ensure the CIA (confidentiality, integrity and accessibility) security model of the networks security and high efficiency of performance results in various resource-constrained applications and environments of the IoT platform, DDO-(data-driven operation) based constructions have been introduced as a primitive design that meet the demand of high speed encryption systems. Among of them, the TMN-family ciphers which were proposed by Tuan P.M., Do Thi B., etc., in 2016, are entirely suitable approaches for various communication applications of wireless mobile networks (WMNs) and advanced wireless sensor networks (WSNs) with high flexibility, applicability and mobility shown in two different algorithm selections, TMN64 and TMN128. The two ciphers provide strong security against known cryptanalysis, such as linear attacks and differential attacks. In this study, we demonstrate new probability results on the security of the two TMN construction versions - TMN64 and TMN128, by proposing efficient related-key recovery attacks. The high probability characteristics (DCs) are constructed under the related-key differential properties on a full number of function rounds of TMN64 and TMN128, as 10-rounds and 12-rounds, respectively. Hence, the amplified boomerang attacks can be applied to break these two ciphers with appropriate complexity of data and time consumptions. The work is expected to be extended and improved with the latest BCT technique for better cryptanalytic results in further research.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.6
• /
• pp.1287-1294
• /
• 2021

This paper is a study on the implementation of a sensor-based smart compression system for improving home and street environments. Since modernization, the amount of garbage has been increasing every year, and this has seriously adversely affected not only people but also ecosystems such as marine pollution and soil pollution. In particular, in large cities with large floating populations, garbage is dumped on the streets without proper measures to deal with the amount of waste generated. In order to improve this problem, this paper intends to implement a system with automatic compression and opening/closing functions using sensors. This system is designed to activate automatic opening/closing function through an infrared sensor, and automatically opening and closing when the inclination is changed using an impact sensor. In addition, by installing a distance sensor, the amount of internal waste can be easily monitored from the outside, and a manual compression switch and a manual opening/closing switch is separately designed to enable opening and closing and compression as needed to increase the effectiveness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.199-201
• /
• 2021

The Internet of Things (IoT) is a technology that can organically connect people and things without time and space constraints by using communication network technology and sensors, and transmit and receive data in real time. The IoT used in all industrial fields has limitations in terms of storage allocation, such as device size, memory capacity, and data transmission performance, so it is important to manage power consumption to effectively utilize the limited battery capacity. In the prior research, there is a problem in that security is deteriorated instead of improving power efficiency by lightening the security algorithm of the encryption module. In this study, we proposes a low-power security architecture that can utilize high-performance security algorithms in the IoT environment. This can provide high security and power efficiency by using relatively complex security modules in low-power environments by executing security modules only when threat detection is required based on inspection results.

• Journal of Internet of Things and Convergence
• /
• v.10 no.1
• /
• pp.53-58
• /
• 2024

IoT, Big-data, AI, and Cloud technologies, which are core technologies of the 4th Industrial Revolution, have recently been applied to various fields and are being used as core technologies for new growth engines. Accordingly, these core technologies are applied to the agricultural field without exception, contributing to solving the problem of labor shortage, reducing production costs, and reducing environmental burden through remote and automated production without time and space constraints. However, as these core technologies are utilized, security incidents are occurring in the agricultural field as well. Accordingly, this study divides smart farms into three stages(Basic, Middle, and High) and presents the characteristics and security threats of each stage. In particular, as the number of container-based services and research increases under cloud platforms, we would like to suggest countermeasures focusing on security threats.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.6
• /
• pp.1299-1306
• /
• 2023

In this paper, we present a system for undesignated cultural heritage management and real-time theft chase, which uses flash-based large-capacity storage. The proposed system is composed of 3 parts, such as a cultural management device, a flash-based server, and a monitoring service for managing cultural heritages and chasing thefts using IoT technologies. However flash-based storage needs methods to overcome the limited lifespan. Therefore, in this paper, we present a system, which uses the disk buffer in flash-based storage to overcome the disadvantage, and evaluate the system performance in various environments. In our experiments, LRU policy shows the number of direct writes in the flash-based storage by 10.7% on average compared with CLOCK and FCFS.

• Convergence Security Journal
• /
• v.24 no.1
• /
• pp.11-20
• /
• 2024

Recently, smart buildings that can efficiently manage energy using ICT technology and operate and control through the building automation system by collecting data from a large number of IoT sensors in real time are attracting attention. However, as data management is carried out through an open environment, the safety of smart buildings is threatened by the security vulnerability of the existing building automation protocol. Therefore, in this paper, we analyze the major data link technology of BACnet, which is used universally, and propose OWE-based efficient BACnet/SC that can ensure the reliability of data in a wireless environment. The proposed protocol enables safe communication even in an open network by applying OWE and provides the same level of security as BACnet/SC in a TLS environment. As a result, it reduces the connection process twice and reduces the average time required by 40%, enabling more efficient communication than before.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.19 no.4
• /
• pp.771-780
• /
• 2024

In this study, we implemented a real-time pest detection and prediction system for a strawberry farm using a computer vision model based on the YOLOv5 architecture and an Isolation Forest Classifier. The model performance evaluation showed that the YOLOv5 model achieved a mean average precision (mAP 0.5) of 78.7%, an accuracy of 92.8%, a recall of 90.0%, and an F1-score of 76%, indicating high predictive performance. This system was designed to be applicable not only to strawberry farms but also to other crops and various environments. Based on data collected from a tomato farm, a new AI model was trained, resulting in a prediction accuracy of over 85% for major diseases such as late blight and yellow leaf curl virus. Compared to the previous model, this represented an improvement of more than 10% in prediction accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.4
• /
• pp.433-440
• /
• 2016

This paper proposes a method of minimizing total energy consumption of IoT environment when communication devices in the network share the information directly. The proposed method reduces total number of transmission for the information sharing by using an effective network coding-based technique which dynamically selects a node and a data packet for each transmission. Simulation results show that the proposed method has better performance than an existing network coding-based method selecting transmission node in fixed order, a network coding-based method selecting transmission node in random order, and a uncoded method selecting transmission node in random order.