• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.179-192
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• 2023

The widespread use of Cloud Computing, Internet of Things (IoT), and social media in the Information Communication Technology (ICT) field has resulted in continuous and unavoidable cyber-attacks on users and critical infrastructures worldwide. Traditional security measures such as firewalls and encryption systems are not effective in countering these sophisticated cyber-attacks. Therefore, Intrusion Detection and Prevention Systems (IDPS) are necessary to reduce the risk to an absolute minimum. Although IDPSs can detect various types of cyber-attacks with high accuracy, their performance is limited by a high false alarm rate. This study proposes a new technique called Fuzzy Logic - Objective Risk Analysis (FLORA) that can significantly reduce false positive alarm rates and maintain a high level of security against serious cyber-attacks. The FLORA model has a high fuzzy accuracy rate of 90.11% and can predict vulnerabilities with a high level of certainty. It also has a mechanism for monitoring and recording digital forensic evidence which can be used in legal prosecution proceedings in different jurisdictions.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1029-1035
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• 2019

In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate movie-based recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

• Electronics and Telecommunications Trends
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• v.33 no.1
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• pp.101-110
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• 2018

Based on the main technologies of the 4th Industrial Revolution, industries including the smart home, transportation, agriculture, factory, energy, and medical care industries are rapidly developing. Disaster management technologies and services based on state-of-the-art convergence technologies are being widely applied for the purposes of public safety. State-of-the-art scientific technologies including the Internet of Things (IoT) are expected to offer alternative solutions to pending issues of disaster and safety. Particularly in disaster management, a "prevention activity"to avoid and control disasters in advance is essential, and thus disaster prevention and safety monitoring technologies based on hyper-connected intelligence are fundamental for society during the 4th Industrial Revolution. IoT technologies are being actively applied and utilized in various fields to prevent social and natural disasters. In this article, we introduce the development trends of disaster prevention and safety monitoring technologies based on IoT technologies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.781-782
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• 2015

As growth engines such as cloud, social networks, big data that can affect the security market have been grown, the information security industry has has also rapidly evolved. Reviewing information security policies carried out in USA, UK and Japan, this paper examines trends on the IoT-related information protection law and regulations that are at issue around the major developed countries. Through this research, we can get the implication that measures be taken as soon as possible to apply the existing data protection laws in the Internet of Things.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.76-85
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• 2018

In recent years, automobiles have evolved from simple transportation to convergence devices, and have combined the Internet of things, high-speed communications, and artificial intelligence technologies to provide people with social and cultural benefits. To provide services such as a smart traffic analysis, autonomous driving, and unmanned driving, automobiles applying these technologies are required to perform various types of sensing and image analyses for vehicle recognition and distance measurements. addition, there has been a rapid increase in the need to introduce an automotive Ethernet, that can provide a wide bandwidth to support. such technologies. In this article, we survey the latest trends in automotive Ethernet based automobiles and their security threats, and analyze the status and prospects of security technologies applied to cope with them.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.277-278
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• 2014

사물인터넷(IoT)은 '개방형 환경에서 인터넷을 기반으로 사람, 사물, 데이터 및 프로세스를 서로 연결하여 정보를 교류하고 상호 소통하는 지능형 인프라'로서 홈 가전, 교통 물류, 건설, 에너지, 헬스케어, 사회안전 등 여러 분야에서 새로운 상품을 개발하고 공급해 창조경제의 핵심동력 가운데 하나가 될 것으로 기대된다. 그러나 네트워크, 서비스, 플랫폼/디바이스 등 기반 환경에서 다양한 개인정보 침해에 대한 위협이 존재하며 개인정보 보호와 기술 활용이라는 이슈에 관한 논의는 아직 초기 단계에 있다. 따라서 본 연구에서는 IoT 환경에서 정보주체의 민감한 개인정보에 대한 안전한 보호 정책 적용과 효율적 정보기술 활용 및 제공이 가능한 개인정보보호 프레임워크를 제안하고자 한다.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.86-94
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• 2018

Information-Centric Networking (ICN) has been recognized as a new networking technology for the upcoming data-centric 4th industrial revolution based society. In addition, it has noted that Pub/Sub-style communication is rapidly growing in areas including big data processing and microservice as well as the existing Internet of Things and social networking technologies. Therefore, ICN is highly needed to efficiently support Pub/Sub-style communication for successful deployment as a next-generation network infrastructure technology. This paper summarizes the recent research trends of Pub/Sub communication technologies over ICN, and discusses future research issues.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.548-549
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• 2016

노령인구와 사회 취약 계층을 지원하기 위해 사회복지에 대한 사회적 노력이 확대되고 있으며, 또한 사물인터넷 (Internet of Things: loT)이란 IT 기술의 발전을 통해 사회복지 체계를 효율적으로 지원할 수 있는 기회가 마련되었다. 사물인터넷은 사물들로부터 수집한 정보를 분석 및 처리함으로써 다양한 지능 서비스 제공이 가능하기 때문에 그 활용도가 점차 증대되고 있다. 그러나 기존 사물인터넷 기반 사회취약 계층 서비스들은 Healthcare 서비스에 초점을 맞추고 있으며, 이는 사회복지 전 분야에 대한 효율적인 서비스 제공에 어려움을 주게 된다. 따라서 사회복지 체계에 대한 효과적인 지원을 위해 IT 융합 기반 기술이 제공되어야 하며, 본 논문에서는 사회복지 체계를 효율적으로 지원할 수 있는 서비스를 제공하기 위한 소프트웨어 플랫폼을 제안한다. 제안된 플랫폼은 loT 장치와 스마트 폰으로부터 정보를 수집하고 처리하여 이를 기반으로 다양한 사회복지 서비스 지원한다.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.135-155
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• 2024

Urban public health monitoring in smart cities focuses on the control of conditions and health challenges in urban environments. Considering the rapid spread of diseases and pandemics, it is important for health authorities to trace people carrying the virus. In smart cities, this tracing must be interoperable and intelligent, especially in indoor surfaces characterized by small distances between people. Therefore, to fight pandemics, it is necessary to start with the already-existing digital equipment of the Internet of Things, such as connected objects and smartphones. In this study, the developed system is employed to provide a social IoT network and suggest a strategy which allows reliable traceability without threatening the privacy of users. This IoT-based system allows respecting the social distance between persons sharing public services in smart cities without applying smartphone applications or severe confinement. It also permits a return to normal life in case of viral pandemic and ensures the much-desired balance between economy and health. The present study analyses previous proposed social distance systems then, unlike these studies, suggests an intelligent and distributed IoT based strategy for positioning students. Two scenarios of static and dynamic optimization-based placement of Bluetooth Low Energy devices are proposed and an experimental study shows the contribution and complementarity of the introduced contact tracing strategy with the applications on smartphones.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.112-119
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• 2023

Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.