Background/Objectives: As the financial market becomes more and more complicated and specialized ... more Background/Objectives: As the financial market becomes more and more complicated and specialized due to development of IT technologies and globalization of the financial environment, financial engineering experts will come into the spotlight with the ability to analyze the situation of the financial market, to prospect the future, and analyze it scientifically and statistically based on mathematical understanding and analysis ability. In this paper, we provide an algorithm to determine the rigidity of braced rectangular frameworks consisting of rectangular array of girder beams and riveted joints. Methods/Statistical analysis: The STEAM education program suggested in this paper will improve the logical 1 International Journal of Pure and Applied Mathematics Volume 118 No. 19 2018, 2169-2182 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu Special Issue ijpam.eu
Summary. Recently, mobile RFID (Radio Frequency Identification) services such as in smart poster ... more Summary. Recently, mobile RFID (Radio Frequency Identification) services such as in smart poster or supply chain are rapidly growing up as a newly generating industry. Here, mobile RFID service is defined as a special type of mobile service using RFID tag packaging object and RFID reader attached mobile RFID terminal. This paper is to provide an approach for ensuring RFID net-work security based on security engineering method. To ensure secure mobile RFID service network, we describes an approach which includes security state and security flow. We propose an efficient phone-based middleware platform architecture which is constructed by mobile RFID security mechanism based on WIPI (Wireless Internet Platform for Interoperability). WIPI-based light-weight mobile RFID security platform can be applied to various mobile RFID services that need secure business in mobile environment. So, we will propose the way to protect the personal privacy effectively using privacy preference for secure...
Due to the COVID-19 lockdown, public education has been forced to hold classes online, which incr... more Due to the COVID-19 lockdown, public education has been forced to hold classes online, which increases the time students are on the internet at home. While this situation has significantly reduced the incidence of physical violence between students, cyberbullying has increased sharply, even among younger students. This paper examines a program developed to educate elementary school students on how to best respond to cyberbullying—a social issue that hinders the achievement of sustainable development goals (SDGs). The program was applied to students, and the educational effects were tracked. First, we analyzed education programs in South Korea and the United States that teach students how to cope with cyberbullying, extracted characteristic parts, and developed the online education program in accordance with the current situation in South Korea. Next, we conducted an online education preference survey through an independent sample t-test and one-way ANOVA. As a result, regardless of ...
Attackers’ intrusion into the Enterprise LAN is increasing every year, and the method is becoming... more Attackers’ intrusion into the Enterprise LAN is increasing every year, and the method is becoming more intelligent and crafty. Various security measures against external network intrusions, such as firewalls, are being studied and applied to protect against external attacks, but it is difficult to respond to increasing attacks. Most institutions block access from the external network for the safety of the internal network and allow access from the internal network to the external network through some restricted ports. In particular, restricted ports in subject to a variety of security techniques to block intrusion into the internal network, but in the process, access to the internal network is only applied by restricted ports, making it inefficient to handle internal requests. Although various studies have been conducted on network isolation to address these challenges, it is difficult to perform tasks efficiently as security functions, such as detecting whether request data is atta...
As the development of technology accelerates, the Fourth Industrial Revolution, which combines va... more As the development of technology accelerates, the Fourth Industrial Revolution, which combines various technologies and provides them as one service, has been in the spotlight, and services using big data, Artificial Intelligence (AI) and Internet of Things (IoT) are becoming more intelligent and helpful to users. As these services are used in various fields, attacks by attackers also occur in various areas and ways. However, cyberattacks by attackers may vary depending on the attacking pattern of the attacker, and the same vulnerability can be attacked from different perspectives. Therefore, in this study, by constructing a cyberattack framework based on preemptive prediction, we can collect vulnerability information based on big data existing on the network and increase the accuracy by applying machine learning to the mapping of keywords frequently mentioned in attack strategies. We propose an attack strategy prediction framework.
Recommendation systems aim to decipher user interests, preferences, and behavioral patterns autom... more Recommendation systems aim to decipher user interests, preferences, and behavioral patterns automatically. However, it becomes trickier to make the most trustworthy and reliable recommendation to users, especially when their hardest earned money is at risk. The credibility of the recommendation is of magnificent importance in crowdfunding project recommendations. This research work devises a hybrid machine learning-based approach for credible crowdfunding projects’ recommendations by wisely incorporating backers’ sentiments and other influential features. The proposed model has four modules: a feature extraction module, a hybrid LDA-LSTM (latent Dirichlet allocation and long short-term memory) based latent topics evaluation module, credibility formulation, and recommendation module. The credibility analysis proffers a process of correlating project creator’s proficiency, reviewers’ sentiments, and their influence to estimate a project’s authenticity level that makes our model robust...
Artificial intelligence (AI) has a limitation in that it is only in the passive cognition area, s... more Artificial intelligence (AI) has a limitation in that it is only in the passive cognition area, so its operating process is not transparent; therefore, the technology relies on learning data. Since raw data for AI learning are processed and inspected manually to assure high quality for sophisticated AI learning, human errors are inevitable, and damaged and incomplete data and differences from the original data may lead to unexpected outputs of AI learning for which processed data are used. In this context, this research examines cases where AI learning data were inaccurate, in terms of cybersecurity, and the need for learning data management before machine learning through analysis of cybersecurity attack techniques, and we propose the direction of establishing a data-preserving AI system, which is a blockchain-based learning data environment model to verify the integrity of learning data. The data-preserving AI learning environment model is expected to prevent cyberattacks and data...
Agriculture and livestock play a vital role in social and economic stability. Food safety and tra... more Agriculture and livestock play a vital role in social and economic stability. Food safety and transparency in the food supply chain are a significant concern for many people. Internet of Things (IoT) and blockchain are gaining attention due to their success in versatile applications. They generate a large amount of data that can be optimized and used efficiently by advanced deep learning (ADL) techniques. The importance of such innovations from the viewpoint of supply chain management is significant in different processes such as for broadened visibility, provenance, digitalization, disintermediation, and smart contracts. This article takes the secure IoT–blockchain data of Industry 4.0 in the food sector as a research object. Using ADL techniques, we propose a hybrid model based on recurrent neural networks (RNN). Therefore, we used long short-term memory (LSTM) and gated recurrent units (GRU) as a prediction model and genetic algorithm (GA) optimization jointly to optimize the par...
Closed-circuit television (CCTV) and video surveillance systems (VSSs) are becoming increasingly ... more Closed-circuit television (CCTV) and video surveillance systems (VSSs) are becoming increasingly more common each year to help prevent incidents/accidents and ensure the security of public places and facilities. The increased presence of VSS is also increasing the number of per capita exposures to CCTV cameras. To help protect the privacy of the exposed objects, attention is being drawn to technologies that utilize intelligent video surveillance systems (IVSSs). IVSSs execute a wide range of surveillance duties—from simple identification of objects in the recorded video data, to understanding and identifying the behavioral patterns of objects and the situations at the incident/accident scenes, as well as the processing of video information to protect the privacy of the recorded objects against leakage. Besides, the recorded privacy information is encrypted and recorded using blockchain technology to prevent forgery of the image. The technology herein proposed (the “proposed mechanis...
The ongoing upsurge of deep learning and artificial intelligence methodologies manifest incredibl... more The ongoing upsurge of deep learning and artificial intelligence methodologies manifest incredible accomplishment in a broad scope of assessing issues in different industries, including the energy sector. In this article, we have presented a hybrid energy forecasting model based on machine learning techniques. It is based on the three machine learning algorithms: extreme gradient boosting, categorical boosting, and random forest method. Usually, machine learning algorithms focus on fine-tuning the hyperparameters, but our proposed hybrid algorithm focuses on the preprocessing using feature engineering to improve forecasting. We also focus on the way to impute a significant data gap and its effect on predicting. The forecasting exactness of the proposed model is evaluated using the regression score, and it depicts that the proposed model, with an R-squared of 0.9212, is more accurate than existing models. For the testing purpose of the proposed energy consumption forecasting model, w...
Wireless communication is essential for the infrastructure of a healthcare system. This bidirecti... more Wireless communication is essential for the infrastructure of a healthcare system. This bidirectional communication is used for data collection and to control message delivery. Wireless communication is applied in industries as well as in our daily lives, e.g., smart cities; however, highly reliable communication may be more difficult in environments with low power consumption, many interferences, or IoT wireless network issues due to resource limitations. In order to solve these problems, we investigated the existing three-party password-authenticated key exchange (3PAKE) and developed an enhanced protocol. Currently, Lu et al presented a 3PAKE protocol to improve the security flaws found in Farash and Attari's protocol. This work revisits the protocol proposed by Lu et al. and demonstrates that, in addition to other security weaknesses, the protocol does not provide user anonymity which is an important issue for healthcare environment, and is not secure against insider attacks...
The video created by a surveillance cameras plays a crucial role in crime prevention and examinat... more The video created by a surveillance cameras plays a crucial role in crime prevention and examinations in smart cities. The closed-circuit television camera (CCTV) is essential for a range of public uses in a smart city; combined with Internet of Things (IoT) technologies they can turn into smart sensors that help to ensure safety and security. However, the authenticity of the camera itself raises issues of building up integrity and suitability of data. In this paper, we present a blockchain-based system to guarantee the trustworthiness of the stored recordings, allowing authorities to validate whether or not a video has been altered. It helps to discriminate fake videos from original ones and to make sure that surveillance cameras are authentic. Since the distributed ledger of the blockchain records the metadata of the CCTV video as well, it is obstructing the chance of forgery of the data. This immutable ledger diminishes the risk of copyright encroachment for law enforcement agenc...
Background/Objectives: As the financial market becomes more and more complicated and specialized ... more Background/Objectives: As the financial market becomes more and more complicated and specialized due to development of IT technologies and globalization of the financial environment, financial engineering experts will come into the spotlight with the ability to analyze the situation of the financial market, to prospect the future, and analyze it scientifically and statistically based on mathematical understanding and analysis ability. In this paper, we provide an algorithm to determine the rigidity of braced rectangular frameworks consisting of rectangular array of girder beams and riveted joints. Methods/Statistical analysis: The STEAM education program suggested in this paper will improve the logical 1 International Journal of Pure and Applied Mathematics Volume 118 No. 19 2018, 2169-2182 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu Special Issue ijpam.eu
Summary. Recently, mobile RFID (Radio Frequency Identification) services such as in smart poster ... more Summary. Recently, mobile RFID (Radio Frequency Identification) services such as in smart poster or supply chain are rapidly growing up as a newly generating industry. Here, mobile RFID service is defined as a special type of mobile service using RFID tag packaging object and RFID reader attached mobile RFID terminal. This paper is to provide an approach for ensuring RFID net-work security based on security engineering method. To ensure secure mobile RFID service network, we describes an approach which includes security state and security flow. We propose an efficient phone-based middleware platform architecture which is constructed by mobile RFID security mechanism based on WIPI (Wireless Internet Platform for Interoperability). WIPI-based light-weight mobile RFID security platform can be applied to various mobile RFID services that need secure business in mobile environment. So, we will propose the way to protect the personal privacy effectively using privacy preference for secure...
Due to the COVID-19 lockdown, public education has been forced to hold classes online, which incr... more Due to the COVID-19 lockdown, public education has been forced to hold classes online, which increases the time students are on the internet at home. While this situation has significantly reduced the incidence of physical violence between students, cyberbullying has increased sharply, even among younger students. This paper examines a program developed to educate elementary school students on how to best respond to cyberbullying—a social issue that hinders the achievement of sustainable development goals (SDGs). The program was applied to students, and the educational effects were tracked. First, we analyzed education programs in South Korea and the United States that teach students how to cope with cyberbullying, extracted characteristic parts, and developed the online education program in accordance with the current situation in South Korea. Next, we conducted an online education preference survey through an independent sample t-test and one-way ANOVA. As a result, regardless of ...
Attackers’ intrusion into the Enterprise LAN is increasing every year, and the method is becoming... more Attackers’ intrusion into the Enterprise LAN is increasing every year, and the method is becoming more intelligent and crafty. Various security measures against external network intrusions, such as firewalls, are being studied and applied to protect against external attacks, but it is difficult to respond to increasing attacks. Most institutions block access from the external network for the safety of the internal network and allow access from the internal network to the external network through some restricted ports. In particular, restricted ports in subject to a variety of security techniques to block intrusion into the internal network, but in the process, access to the internal network is only applied by restricted ports, making it inefficient to handle internal requests. Although various studies have been conducted on network isolation to address these challenges, it is difficult to perform tasks efficiently as security functions, such as detecting whether request data is atta...
As the development of technology accelerates, the Fourth Industrial Revolution, which combines va... more As the development of technology accelerates, the Fourth Industrial Revolution, which combines various technologies and provides them as one service, has been in the spotlight, and services using big data, Artificial Intelligence (AI) and Internet of Things (IoT) are becoming more intelligent and helpful to users. As these services are used in various fields, attacks by attackers also occur in various areas and ways. However, cyberattacks by attackers may vary depending on the attacking pattern of the attacker, and the same vulnerability can be attacked from different perspectives. Therefore, in this study, by constructing a cyberattack framework based on preemptive prediction, we can collect vulnerability information based on big data existing on the network and increase the accuracy by applying machine learning to the mapping of keywords frequently mentioned in attack strategies. We propose an attack strategy prediction framework.
Recommendation systems aim to decipher user interests, preferences, and behavioral patterns autom... more Recommendation systems aim to decipher user interests, preferences, and behavioral patterns automatically. However, it becomes trickier to make the most trustworthy and reliable recommendation to users, especially when their hardest earned money is at risk. The credibility of the recommendation is of magnificent importance in crowdfunding project recommendations. This research work devises a hybrid machine learning-based approach for credible crowdfunding projects’ recommendations by wisely incorporating backers’ sentiments and other influential features. The proposed model has four modules: a feature extraction module, a hybrid LDA-LSTM (latent Dirichlet allocation and long short-term memory) based latent topics evaluation module, credibility formulation, and recommendation module. The credibility analysis proffers a process of correlating project creator’s proficiency, reviewers’ sentiments, and their influence to estimate a project’s authenticity level that makes our model robust...
Artificial intelligence (AI) has a limitation in that it is only in the passive cognition area, s... more Artificial intelligence (AI) has a limitation in that it is only in the passive cognition area, so its operating process is not transparent; therefore, the technology relies on learning data. Since raw data for AI learning are processed and inspected manually to assure high quality for sophisticated AI learning, human errors are inevitable, and damaged and incomplete data and differences from the original data may lead to unexpected outputs of AI learning for which processed data are used. In this context, this research examines cases where AI learning data were inaccurate, in terms of cybersecurity, and the need for learning data management before machine learning through analysis of cybersecurity attack techniques, and we propose the direction of establishing a data-preserving AI system, which is a blockchain-based learning data environment model to verify the integrity of learning data. The data-preserving AI learning environment model is expected to prevent cyberattacks and data...
Agriculture and livestock play a vital role in social and economic stability. Food safety and tra... more Agriculture and livestock play a vital role in social and economic stability. Food safety and transparency in the food supply chain are a significant concern for many people. Internet of Things (IoT) and blockchain are gaining attention due to their success in versatile applications. They generate a large amount of data that can be optimized and used efficiently by advanced deep learning (ADL) techniques. The importance of such innovations from the viewpoint of supply chain management is significant in different processes such as for broadened visibility, provenance, digitalization, disintermediation, and smart contracts. This article takes the secure IoT–blockchain data of Industry 4.0 in the food sector as a research object. Using ADL techniques, we propose a hybrid model based on recurrent neural networks (RNN). Therefore, we used long short-term memory (LSTM) and gated recurrent units (GRU) as a prediction model and genetic algorithm (GA) optimization jointly to optimize the par...
Closed-circuit television (CCTV) and video surveillance systems (VSSs) are becoming increasingly ... more Closed-circuit television (CCTV) and video surveillance systems (VSSs) are becoming increasingly more common each year to help prevent incidents/accidents and ensure the security of public places and facilities. The increased presence of VSS is also increasing the number of per capita exposures to CCTV cameras. To help protect the privacy of the exposed objects, attention is being drawn to technologies that utilize intelligent video surveillance systems (IVSSs). IVSSs execute a wide range of surveillance duties—from simple identification of objects in the recorded video data, to understanding and identifying the behavioral patterns of objects and the situations at the incident/accident scenes, as well as the processing of video information to protect the privacy of the recorded objects against leakage. Besides, the recorded privacy information is encrypted and recorded using blockchain technology to prevent forgery of the image. The technology herein proposed (the “proposed mechanis...
The ongoing upsurge of deep learning and artificial intelligence methodologies manifest incredibl... more The ongoing upsurge of deep learning and artificial intelligence methodologies manifest incredible accomplishment in a broad scope of assessing issues in different industries, including the energy sector. In this article, we have presented a hybrid energy forecasting model based on machine learning techniques. It is based on the three machine learning algorithms: extreme gradient boosting, categorical boosting, and random forest method. Usually, machine learning algorithms focus on fine-tuning the hyperparameters, but our proposed hybrid algorithm focuses on the preprocessing using feature engineering to improve forecasting. We also focus on the way to impute a significant data gap and its effect on predicting. The forecasting exactness of the proposed model is evaluated using the regression score, and it depicts that the proposed model, with an R-squared of 0.9212, is more accurate than existing models. For the testing purpose of the proposed energy consumption forecasting model, w...
Wireless communication is essential for the infrastructure of a healthcare system. This bidirecti... more Wireless communication is essential for the infrastructure of a healthcare system. This bidirectional communication is used for data collection and to control message delivery. Wireless communication is applied in industries as well as in our daily lives, e.g., smart cities; however, highly reliable communication may be more difficult in environments with low power consumption, many interferences, or IoT wireless network issues due to resource limitations. In order to solve these problems, we investigated the existing three-party password-authenticated key exchange (3PAKE) and developed an enhanced protocol. Currently, Lu et al presented a 3PAKE protocol to improve the security flaws found in Farash and Attari's protocol. This work revisits the protocol proposed by Lu et al. and demonstrates that, in addition to other security weaknesses, the protocol does not provide user anonymity which is an important issue for healthcare environment, and is not secure against insider attacks...
The video created by a surveillance cameras plays a crucial role in crime prevention and examinat... more The video created by a surveillance cameras plays a crucial role in crime prevention and examinations in smart cities. The closed-circuit television camera (CCTV) is essential for a range of public uses in a smart city; combined with Internet of Things (IoT) technologies they can turn into smart sensors that help to ensure safety and security. However, the authenticity of the camera itself raises issues of building up integrity and suitability of data. In this paper, we present a blockchain-based system to guarantee the trustworthiness of the stored recordings, allowing authorities to validate whether or not a video has been altered. It helps to discriminate fake videos from original ones and to make sure that surveillance cameras are authentic. Since the distributed ledger of the blockchain records the metadata of the CCTV video as well, it is obstructing the chance of forgery of the data. This immutable ledger diminishes the risk of copyright encroachment for law enforcement agenc...
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