• Title/Summary/Keyword: IoT Device Security

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A Study on Authentication Management and Communication Method using AKI Based Verification System in Smart Home Environment (스마트 홈 환경에서 AKI기반 검증 시스템을 활용한 인증관리 및 통신 기법에 관한 연구)

  • Jin, Byung Wook;Park, Jung Oh;Jun, Moon Seog
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.16 no.6
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    • pp.25-31
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    • 2016
  • With the development of IOT technology and the expansion of ICT services recently, a variety of home network services have been advanced based on wired and wireless high speed telecommunication. Domestic and global companies have been studying on the innovative technology for the users using IOT based technology and the environment for the smart home services has been gradually developed. The users live their lives with more convenience due to the expansions and developments of smart phones. However, the threatening on the security of the smart home network had occurred by various attacks with the connection to the smart environment telecommunication, lack of applications on low powered and light weight telecommunication, and the problems of security guideline. In addition, the solutions are required for the new and variant attacking cases such as data forgery and alteration of the device for disguising approach with ill will. In this article, the safe communication protocol was designed using certification management technique based on AKI which supplemented the weakness of PKI, the existing certification system in the smart environment. Utilizing the signature technique based on ECDSA, the efficiency on the communication performance was improved, and the security and the safety were analyzed on the security threat under the smart home environment.

A study on machine learning-based defense system proposal through web shell collection and analysis (웹쉘 수집 및 분석을 통한 머신러닝기반 방어시스템 제안 연구)

  • Kim, Ki-hwan;Shin, Yong-tae
    • Journal of Internet Computing and Services
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    • v.23 no.4
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    • pp.87-94
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    • 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.

A Study on People Counting in Public Metro Service using Hybrid CNN-LSTM Algorithm (Hybrid CNN-LSTM 알고리즘을 활용한 도시철도 내 피플 카운팅 연구)

  • Choi, Ji-Hye;Kim, Min-Seung;Lee, Chan-Ho;Choi, Jung-Hwan;Lee, Jeong-Hee;Sung, Tae-Eung
    • Journal of Intelligence and Information Systems
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    • v.26 no.2
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    • pp.131-145
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    • 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.

A Study on u-Care Service for the Health and Safety of the Elderly Living Alone (1인 가구 고령자의 건강과 안전을 위한 u-Care에 관한 연구)

  • Kang, Seungae
    • Convergence Security Journal
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    • v.17 no.3
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    • pp.59-64
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    • 2017
  • Korea is experiencing a rapid increase in the number of elderly living alone accompanying the aging society problem, a nd is making efforts to solve the problem through the policy of 'living alone u-care service'. The purpose of this study is to propose a better u-Care service improvement method by applying new technology to improve the user experience of ucare service for the health and safety of the elderly living alone. First, the improvement of u-Care service for elderly livin g alone by applying IoT technology. It provides remote monitoring service using health information data measured through wearable device, and transmits personal health status to medical institution by using personal device such as smart phone, so that remote medical consultation or telemedicine can be connected in the future. Second, improvement of u-Care service through consideration of emotional stability of elderly living alone as well as simple safety and health care through applica tion of emotional service robot technology.It is expected that it will be able to help independent living of one person's elde rly person in the future by providing caring function service to existing u-care service providing service.

Privacy Vulnerability Analysis on Shuai et al.'s Anonymous Authentication Scheme for Smart Home Environment (Shuai등의 스마트 홈 환경을 위한 익명성 인증 기법에 대한 프라이버시 취약점 분석)

  • Choi, Hae-Won;Kim, Sangjin;Jung, Young-Seok;Ryoo, Myungchun
    • Journal of Digital Convergence
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    • v.18 no.9
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    • pp.57-62
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    • 2020
  • Smart home based on Internet of things (IoT) is rapidly emerging as an exciting research and industry field. However, security and privacy have been critical issues due to the open feature of wireless communication channel. As a step towards this direction, Shuai et al. proposed an anonymous authentication scheme for smart home environment using Elliptic curve cryptosystem. They provided formal proof and heuristic analysis and argued that their scheme is secure against various attacks including de-synchronization attack, mobile device loss attack and so on, and provides user anonymity and untraceability. However, this paper shows that Shuai et al.'s scheme does not provide user anonymity nor untraceability, which are very important features for the contemporary IoT network environment.

Internet of Things for in Home Health based Monitoring System: Modern Advances, Challenges and Future Directions

  • Omer Iqbal;Tayyeba Iftakhar;Saleem Zubair Ahmad
    • International Journal of Computer Science & Network Security
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    • v.24 no.8
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    • pp.191-204
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    • 2024
  • IOT has carried out important function in converting the traditional fitness care corporation. With developing call for in population, traditional healthcare structures have reached their outmost functionality in presenting sufficient and as plenty as mark offerings. The worldwide is handling devastating developing antique population disaster and the right want for assisted-dwelling environments is turning into inevitable for senior citizens. There furthermore a determination by means of the use of way of countrywide healthcare organizations to increase crucial manual for individualized, right blanketed care to prevent and manipulate excessive coronial situations. Many tech orientated packages related to Health Monitoring have been delivered these days as taking advantage of net boom everywhere on globe, manner to improvements in cellular and in IOT generation. Such as optimized indoor networks insurance, community shape, and fairly-low device fee performances, advanced tool reliability, low device energy consumption, and hundreds higher unusual common usual performance in network safety and privacy. Studies have highlighted fantastic advantages of integrating IOT with health care location and as era is improving the rate also cannot be that terrific of a problem. However, many challenges in this new paradigm shift notwithstanding the fact that exist, that need to be addressed. So the out most purpose of this research paper is 3 essential departments: First, evaluation of key elements that drove the adoption and boom of the Internet of factors based totally domestic some distance off monitoring; Second, present fashionable improvement of IOT in home a long manner off monitoring shape and key building gadgets; Third, communicate future very last effects and distinct guidelines of such type a long way off monitoring packages going ahead. Such Research is a wonderful manner in advance now not outstanding in IOT Terminology but in standard fitness care location.

Study on the Connection with Public Authentication and Bio Authentication (공인인증서와 바이오인증 연계를 위한 연구)

  • Ryu, Gab-Sang
    • Journal of Internet of Things and Convergence
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    • v.1 no.1
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    • pp.39-44
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    • 2015
  • Organization is increasing the authorizing process to use public certificate and bio information. Certificate, has evolved to be able to parallel distributes the bio authentication and portable bio-authentication device. Authentication using an individual's PC and smart devices continue to generalize, while convenience for authentication is increased by comparison Study on cooperation with the security at the network level's a weak situation. If ask authentication method through the cooperation of the public certificate and bio information work with current network access control, there is a possibility to develop a more powerful security policy. by cooperation weaknesses against vulnerable personal authentication techniques on security token in a reliable and secure personal authentication techniques, such as bio-recognition, Bio Information for identification and to prevent exposing a methodology suggest to validate whether or not to carry out in this paper. In addition, organize the scenario that can work with the 802.1x network authentication method, and presented a proposal aimed at realization.

The Design of Smart Factory System using AI Edge Device (AI 엣지 디바이스를 이용한 스마트 팩토리 시스템 설계)

  • Han, Seong-Il;Lee, Dae-Sik;Han, Ji-Hwan;Shin, Han Jae
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.15 no.4
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    • pp.257-270
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    • 2022
  • In this paper, we design a smart factory risk improvement system and risk improvement method using AI edge devices. The smart factory risk improvement system collects, analyzes, prevents, and promptly responds to the worker's work performance process in the smart factory using AI edge devices, and can reduce the risk that may occur during work with improving the defect rate when workers perfom jobs. In particular, based on worker image information, worker biometric information, equipment operation information, and quality information of manufactured products, it is possible to set an abnormal risk condition, and it is possible to improve the risk so that the work is efficient and for the accurate performance. In addition, all data collected from cameras and IoT sensors inside the smart factory are processed by the AI edge device instead of all data being sent to the cloud, and only necessary data can be transmitted to the cloud, so the processing speed is fast and it has the advantage that security problems are low. Additionally, the use of AI edge devices has the advantage of reducing of data communication costs and the costs of data transmission bandwidth acquisition due to decrease of the amount of data transmission to the cloud.

A Design of Smart Sensor Framework for Smart Home System Bsed on Layered Architecture (계층 구조에 기반을 둔 스마트 홈 시스템를 위한 스마트 센서 프레임워크의 설계)

  • Chung, Won-Ho;Kim, Yu-Bin
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.4
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    • pp.49-59
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    • 2017
  • Smart sensing plays a key role in a variety of IoT applications, and its importance is growing more and more together with the development of artificial intelligence. Therefore the importance of smart sensors cannot be overemphasized. However, most studies related to smart sensors have been focusing on specific application purposes, for example, security, energy saving, monitoring, and there are not much effort on researches on how to efficiently configure various types of smart sensors to be needed in the future. In this paper, a component-based framework with hierarchical structure for efficient construction of smart sensor is proposed and its application to smart home is designed and implemented. The proposed method shows that various types of smart sensors to be appeared in the near future can be configured through the design and development of necessary components within the proposed software framework. In addition, since it has a layered architecture, the configuration of the smart sensor can be expanded by inserting the internal or external layers. In particular, it is possible to independently design the internal and external modules when designing an IoT application service through connection with the external device layer. A small-scale smart home system is designed and implemented using the proposed method, and a home cloud operating as an external layer, is further designed to accommodate and manage multiple smart homes. By developing and thus adding the components of each layer, it will be possible to efficiently extend the range of applications such as smart cars, smart buildings, smart factories an so on.

Predictive maintenance architecture development for nuclear infrastructure using machine learning

  • Gohel, Hardik A.;Upadhyay, Himanshu;Lagos, Leonel;Cooper, Kevin;Sanzetenea, Andrew
    • Nuclear Engineering and Technology
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    • v.52 no.7
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    • pp.1436-1442
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    • 2020
  • Nuclear infrastructure systems play an important role in national security. The functions and missions of nuclear infrastructure systems are vital to government, businesses, society and citizen's lives. It is crucial to design nuclear infrastructure for scalability, reliability and robustness. To do this, we can use machine learning, which is a state of the art technology used in various fields ranging from voice recognition, Internet of Things (IoT) device management and autonomous vehicles. In this paper, we propose to design and develop a machine learning algorithm to perform predictive maintenance of nuclear infrastructure. Support vector machine and logistic regression algorithms will be used to perform the prediction. These machine learning techniques have been used to explore and compare rare events that could occur in nuclear infrastructure. As per our literature review, support vector machines provide better performance metrics. In this paper, we have performed parameter optimization for both algorithms mentioned. Existing research has been done in conditions with a great volume of data, but this paper presents a novel approach to correlate nuclear infrastructure data samples where the density of probability is very low. This paper also identifies the respective motivations and distinguishes between benefits and drawbacks of the selected machine learning algorithms.