The tandem metal inert gas (MIG) process uses two wires that are continuously fed through a speci... more The tandem metal inert gas (MIG) process uses two wires that are continuously fed through a special welding torch and disbursed to form a single molten pool. Within the contact tip of the modern approach, the wires are electrically insulated from one another. This study identified the effect of welding electrode spacing on the distortion of AA5052 aluminum plates and different mechanical properties including hardness and thermal cycle using grey relational analysis. Plate distortion was subsequently predicted using the grey prediction model GM (1, 6). This research used a pair of 400 mm × 75 mm × 5 mm of AA5052 plates and electrode distances of 18, 27, and 36 mm. The welding current, voltage, welding speed, and argon flow rate were 130 A, 23 V, 7 mm/s, and 17 L/min, respectively. The temperature was measured using a type-K thermocouple at 10, 20, 30, and 40 mm from the center of the weld bead. The smallest distortion at an electrode distance of 27 mm was 1.4 mm. At an electrode dist...
JOIV : International Journal on Informatics Visualization
Pulse palpation is one of the non-invasive patient observations that identify patient conditions ... more Pulse palpation is one of the non-invasive patient observations that identify patient conditions based on the shape of the human pulse. The observations have been practiced by Traditional Chinese Medicine (TCM) practitioners since thousands of years ago. The practitioners measure the patient’s arterial pulses in three points of both patient wrists called chun, guan, and chy, then diagnose based on their knowledge and experience. Pulse-Line Intersection (PLI) method extract features of each pulse from the observed pulse wave sequence. PLI is performed by summing the number of intersections between the artificial line and the pulse wave. The method is proven in differentiating between hesitant with moderate pulse waves. As the method implemented in Clinical Decision Support System (CDSS) related to pulse palpation, some outlier data might emerge and affect the measurement result. Thus, outlier filtering is needed to prevent unnecessary prediction processes by machine learning (ML) mod...
Advances in information technology (IT) and operation technology (OT) accelerate the development ... more Advances in information technology (IT) and operation technology (OT) accelerate the development of manufacturing systems (MS) consisting of integrated circuits (ICs), modules, and systems, toward Industry 4.0. However, the existing MS does not support comprehensive identity forensics for the whole system, limiting its ability to adapt to equipment authentication difficulties. Furthermore, the development of trust imposed during their crosswise collaborations with suppliers and other manufacturers in the supply chain is poorly maintained. In this paper, a trust chain framework with a comprehensive identification mechanism is implemented for the designed MS system, which is based and created on the private blockchain in conjunction with decentralized database systems to boost the flexibility, traceability, and identification of the IC-module-system. Practical implementations are developed using a functional prototype. First, the decentralized application (DApp) and the smart contract...
With limited retrieval of reserves and restricted capability in plant pathology, automation of pr... more With limited retrieval of reserves and restricted capability in plant pathology, automation of processes becomes essential. All over the world, farmers are struggling to prevent various harm from bacteria or pathogens such as viruses, fungi, worms, protozoa, and insects. Deep learning is currently widely used across a wide range of applications, including desktop, web, and mobile. In this study, the authors attempt to implement the function of AlexNet modification architecture-based CNN on the Android platform to predict tomato diseases based on leaf image. A dataset with of 18,345 training data and 4,585 testing data was used to create the predictive model. The information is separated into ten labels for tomato leaf diseases, each with 64 × 64 RGB pixels. The best model using the Adam optimizer with a realizing rate of 0.0005, the number of epochs 75, batch size 128, and an uncompromising cross-entropy loss function, has a high model accuracy with an average of 98%, a strictness r...
Early prediction of students’ learning performance and analysis of student behavior in a virtual ... more Early prediction of students’ learning performance and analysis of student behavior in a virtual learning environment (VLE) are crucial to minimize the high failure rate in online courses during the COVID-19 pandemic. Nevertheless, traditional machine learning models fail to predict student performance in the early weeks due to the lack of students’ activities’ data in a week-wise timely manner (i.e., spatiotemporal feature issues). Furthermore, the imbalanced data distribution in the VLE impacts the prediction model performance. Thus, there are severe challenges in handling spatiotemporal features, imbalanced data sets, and a lack of explainability for enhancing the confidence of the prediction system. Therefore, an intelligent framework for explainable student performance prediction (ESPP) is proposed in this study in order to provide the interpretability of the prediction results. First, this framework utilized a time-series weekly student activity data set and dealt with the VLE...
With efficient routing, Wireless Sensor Networks (WSNs) can provide the continuous transmission w... more With efficient routing, Wireless Sensor Networks (WSNs) can provide the continuous transmission with improved lifetime. Different routing protocols account for the different results over the WSNs. WSNs acquire special place in modern day network applications such as body area networks, home animations, cellular enhancement, etc. Especially, focusing on the home automation, a lot of routing algorithms and protocols have been proposed over the years that aim at enhancing the lifetime of such networks. Some of the popular algorithms include Relative Direction Based Sensor Routing (RDSR), Convention Routing (CR), Relative Identification and Direction-Based Sensor Routing (RIDSR), etc. These protocols focus over solving the routing loop problem along with improvement in lifetime of the overall network. However, the gains attained by these networks show a relatively less improvement. Thus, considering the similar problem of routing loop and a lifetime, an energy efficient routing algorith...
The spread of PM2.5 pollutants that endanger health is difficult to predict because it involves m... more The spread of PM2.5 pollutants that endanger health is difficult to predict because it involves many atmospheric variables. These micron particles can spread rapidly from their source to residential areas, increasing the risk of respiratory disease if exposed for long periods. The prediction system of PM2.5 propagation provides more detailed and accurate information as an early warning system to reduce health impacts on the community. According to the idea of transformative computing, the approach we propose in this paper allows computation on the dataset obtained from massive-scale PM2.5 sensor nodes via wireless sensor network. In the scheme, the deep learning model is implemented on the server nodes to extract spatiotemporal features on these datasets. This research was conducted by using dataset of air quality monitoring systems in Taiwan. This study presents a new model based on the convolutional recursive neural network to generate the prediction map. In general, the model is ...
The sparse data in PM2.5 air quality monitoring systems is frequently happened on large-scale sma... more The sparse data in PM2.5 air quality monitoring systems is frequently happened on large-scale smart city sensing applications, which is collected via massive sensors. Moreover, it could be affected by inefficient node deployment, insufficient communication, and fragmented records, which is the main challenge of the high-resolution prediction system. In addition, data privacy in the existing centralized air quality prediction system cannot be ensured because the data which are mined from end sensory nodes constantly exposed to the network. Therefore, this paper proposes a novel edge computing framework, named Federated Compressed Learning (FCL), which provides efficient data generation while ensuring data privacy for PM2.5 predictions in the application of smart city sensing. The proposed scheme inherits the basic ideas of the compression technique, regional joint learning, and considers a secure data exchange. Thus, it could reduce the data quantity while preserving data privacy. Th...
Walking has been demonstrated to improve health in people with diabetes and peripheral arterial d... more Walking has been demonstrated to improve health in people with diabetes and peripheral arterial disease. However, continuous walking can produce repeated stress on the plantar foot and cause a high risk of foot ulcers. In addition, a higher walking intensity (i.e., including different speeds and durations) will increase the risk. Therefore, quantifying the walking intensity is essential for rehabilitation interventions to indicate suitable walking exercise. This study proposed a machine learning model to classify the walking speed and duration using plantar region pressure images. A wearable plantar pressure measurement system was used to measure plantar pressures during walking. An Artificial Neural Network (ANN) was adopted to develop a model for walking intensity classification using different plantar region pressure images, including the first toe (T1), the first metatarsal head (M1), the second metatarsal head (M2), and the heel (HL). The classification consisted of three walki...
Human-centric Computing and Information Sciences, 2017
An infrared transmitting model from the observed finger vein images is proposed in this paper by ... more An infrared transmitting model from the observed finger vein images is proposed in this paper by using multi-light-intensity imaging. This model is estimated from many pixels’ values under different intensity light in the same scene. Due to the fusion method could be applied in biometric system, the vein images of finger captured in the system, we proposed in this paper, will be normalized and preserved the intact of the vein patterns of the biometric data from tested human’s body. From observed pixels under multi-light-intensity, the curve of the transmitting model is recovered by sliding both of the sampled curve segments and using curve-fitting. The fusion method with each pixel level weighting based on the proposed transmitting model curve is adopted by the smooth spatial and estimation of the block quality. Finally, the results shown that our approach is a convenient and practicable approach for the infrared image fusion and subsequent processing for biometric applications.
Recent advances in deep learning have shown many successful stories in smart healthcare applicati... more Recent advances in deep learning have shown many successful stories in smart healthcare applications with data-driven insight into improving clinical institutions’ quality of care. Excellent deep learning models are heavily data-driven. The more data trained, the more robust and more generalizable the performance of the deep learning model. However, pooling the medical data into centralized storage to train a robust deep learning model faces privacy, ownership, and strict regulation challenges. Federated learning resolves the previous challenges with a shared global deep learning model using a central aggregator server. At the same time, patient data remain with the local party, maintaining data anonymity and security. In this study, first, we provide a comprehensive, up-to-date review of research employing federated learning in healthcare applications. Second, we evaluate a set of recent challenges from a data-centric perspective in federated learning, such as data partitioning cha...
2014 Ninth International Conference on Broadband and Wireless Computing, Communication and Applications
Currently, mobile communications are provided convenient methods to explore and communicate with ... more Currently, mobile communications are provided convenient methods to explore and communicate with each other people. A multitude of services have converged on the smartphone platform, and potentially the most notable is social networking. Thus, the electronic Mobile Chat (MC) plays a very important role in the social networking. With the increasingly growing reliance on Mobile Chat System (MCS) in one hand, and the growing number of vulnerabilities and attacks on the other hand, there is an increasingly demand for the security solutions. Despite of the critical role of MCS in the typical Internet mobile user's life, electronic MC services are not so secure. Therefore, the secure End-to-End Mobile Chat (SE2E-MC) scheme is proposed to be one of the suitable solutions. The basic framework for SE2E-MC scheme and its associated requirements are also designed in this paper. The proposal is implemented to provide mutual authentication and prevent the password guessing attack and the undetectable on-line password guessing attack. Finally, the scheme is a password-based authentication and key agreement (AKA) having easy remembered property.
Software defined network (SDN) technology provides potential solutions for the 5G mobile communic... more Software defined network (SDN) technology provides potential solutions for the 5G mobile communication systems. Vehicle-to-vehicle (V2V) communications are the main topology of the Intelligent Transportation System (ITS). Its performance requirement of low latency is one of the most challenging issues. In this study, the transmission latency of V2V communications in software defined vehicular networks (SDVN) is investigated. To minimize the transmission latency in SDVNs, this work proposed five multi-hop routing connection strategies. Simulation results show that under the vehicle density 0.1 ≤ ρ ≤ 0.33, the proposed furthest vehicle (FV) routing algorithm can perform the lowest average transmission latency in SDVNs.
Journal of Electronic Science and Technology, 2019
A peer-to-peer (P2P) multimedia conferencing service is operating that users share their resource... more A peer-to-peer (P2P) multimedia conferencing service is operating that users share their resources to each other on the Internet. It can solve the problem in the centralized conferencing architecture, such as the centralized loading, single point error, and expensive infrastructure. However, P2P networks have the problem that a peer has a difference between the physical location and logical location in the overlay network. In the viewpoint of P2P networks, the nearest conference resource may be far away geographically. The P2P-session initiation protocol (P2P-SIP) multimedia conference is to construct an application-based logical multicast network efficiently according to physical network information. Thus, this paper proposes a real-time streaming relay mechanism for P2P conferences on hierarchical overlay networks. The real-time streaming relay mechanism can improve the transportation efficiency of conferencing stream exchange well based on the application-layer multicast (ALM) st...
Insider threat has attracted considerable attention in security industry. It is difficult to dete... more Insider threat has attracted considerable attention in security industry. It is difficult to detect insiders, because they know organization’s security countermeasures and usually hide their tracks in their normal activities. For evaluating insider detection algorithm on specific organization, it is important to generate a test suite with the corresponding normal activities. However, it is costly and time consuming to generate tailor-made test suite. Due to the complexity of combining different insider attack technique with different organization’s audit data, the insider attack scenario modeling issue arises when adaptively generate test suite for insider threat detection. In this paper, we propose the insider attack frame hierarchy to describe stereotype features of insider attack scenario. The proposed frame-based approach has been combined with the RBAC technologies, and its instantiation property allow us generate the customized insider attack test suite with full test coverage...
Blockchain technology is growing very rapidly, not only in the field of cryptocurrency transactio... more Blockchain technology is growing very rapidly, not only in the field of cryptocurrency transactions but also in other fields such as health care services, service companies, manufacturing. Smart contracts are a series of instruction codes, which automatically verify, execute, and tamper with. With the integration of blockchain technology, it can perform tasks in real time with a high level of security. In this study, we built a smart contract model based on online haggling in determining the purchase of a product. Buyers and sellers haggle with each other for the products they want via online the seller web app. Finally, we propose a smart contract design model using online haggling, which can help provide decision-making in determining the appropriate price from the seller and buyer agreement.
The tandem metal inert gas (MIG) process uses two wires that are continuously fed through a speci... more The tandem metal inert gas (MIG) process uses two wires that are continuously fed through a special welding torch and disbursed to form a single molten pool. Within the contact tip of the modern approach, the wires are electrically insulated from one another. This study identified the effect of welding electrode spacing on the distortion of AA5052 aluminum plates and different mechanical properties including hardness and thermal cycle using grey relational analysis. Plate distortion was subsequently predicted using the grey prediction model GM (1, 6). This research used a pair of 400 mm × 75 mm × 5 mm of AA5052 plates and electrode distances of 18, 27, and 36 mm. The welding current, voltage, welding speed, and argon flow rate were 130 A, 23 V, 7 mm/s, and 17 L/min, respectively. The temperature was measured using a type-K thermocouple at 10, 20, 30, and 40 mm from the center of the weld bead. The smallest distortion at an electrode distance of 27 mm was 1.4 mm. At an electrode dist...
JOIV : International Journal on Informatics Visualization
Pulse palpation is one of the non-invasive patient observations that identify patient conditions ... more Pulse palpation is one of the non-invasive patient observations that identify patient conditions based on the shape of the human pulse. The observations have been practiced by Traditional Chinese Medicine (TCM) practitioners since thousands of years ago. The practitioners measure the patient’s arterial pulses in three points of both patient wrists called chun, guan, and chy, then diagnose based on their knowledge and experience. Pulse-Line Intersection (PLI) method extract features of each pulse from the observed pulse wave sequence. PLI is performed by summing the number of intersections between the artificial line and the pulse wave. The method is proven in differentiating between hesitant with moderate pulse waves. As the method implemented in Clinical Decision Support System (CDSS) related to pulse palpation, some outlier data might emerge and affect the measurement result. Thus, outlier filtering is needed to prevent unnecessary prediction processes by machine learning (ML) mod...
Advances in information technology (IT) and operation technology (OT) accelerate the development ... more Advances in information technology (IT) and operation technology (OT) accelerate the development of manufacturing systems (MS) consisting of integrated circuits (ICs), modules, and systems, toward Industry 4.0. However, the existing MS does not support comprehensive identity forensics for the whole system, limiting its ability to adapt to equipment authentication difficulties. Furthermore, the development of trust imposed during their crosswise collaborations with suppliers and other manufacturers in the supply chain is poorly maintained. In this paper, a trust chain framework with a comprehensive identification mechanism is implemented for the designed MS system, which is based and created on the private blockchain in conjunction with decentralized database systems to boost the flexibility, traceability, and identification of the IC-module-system. Practical implementations are developed using a functional prototype. First, the decentralized application (DApp) and the smart contract...
With limited retrieval of reserves and restricted capability in plant pathology, automation of pr... more With limited retrieval of reserves and restricted capability in plant pathology, automation of processes becomes essential. All over the world, farmers are struggling to prevent various harm from bacteria or pathogens such as viruses, fungi, worms, protozoa, and insects. Deep learning is currently widely used across a wide range of applications, including desktop, web, and mobile. In this study, the authors attempt to implement the function of AlexNet modification architecture-based CNN on the Android platform to predict tomato diseases based on leaf image. A dataset with of 18,345 training data and 4,585 testing data was used to create the predictive model. The information is separated into ten labels for tomato leaf diseases, each with 64 × 64 RGB pixels. The best model using the Adam optimizer with a realizing rate of 0.0005, the number of epochs 75, batch size 128, and an uncompromising cross-entropy loss function, has a high model accuracy with an average of 98%, a strictness r...
Early prediction of students’ learning performance and analysis of student behavior in a virtual ... more Early prediction of students’ learning performance and analysis of student behavior in a virtual learning environment (VLE) are crucial to minimize the high failure rate in online courses during the COVID-19 pandemic. Nevertheless, traditional machine learning models fail to predict student performance in the early weeks due to the lack of students’ activities’ data in a week-wise timely manner (i.e., spatiotemporal feature issues). Furthermore, the imbalanced data distribution in the VLE impacts the prediction model performance. Thus, there are severe challenges in handling spatiotemporal features, imbalanced data sets, and a lack of explainability for enhancing the confidence of the prediction system. Therefore, an intelligent framework for explainable student performance prediction (ESPP) is proposed in this study in order to provide the interpretability of the prediction results. First, this framework utilized a time-series weekly student activity data set and dealt with the VLE...
With efficient routing, Wireless Sensor Networks (WSNs) can provide the continuous transmission w... more With efficient routing, Wireless Sensor Networks (WSNs) can provide the continuous transmission with improved lifetime. Different routing protocols account for the different results over the WSNs. WSNs acquire special place in modern day network applications such as body area networks, home animations, cellular enhancement, etc. Especially, focusing on the home automation, a lot of routing algorithms and protocols have been proposed over the years that aim at enhancing the lifetime of such networks. Some of the popular algorithms include Relative Direction Based Sensor Routing (RDSR), Convention Routing (CR), Relative Identification and Direction-Based Sensor Routing (RIDSR), etc. These protocols focus over solving the routing loop problem along with improvement in lifetime of the overall network. However, the gains attained by these networks show a relatively less improvement. Thus, considering the similar problem of routing loop and a lifetime, an energy efficient routing algorith...
The spread of PM2.5 pollutants that endanger health is difficult to predict because it involves m... more The spread of PM2.5 pollutants that endanger health is difficult to predict because it involves many atmospheric variables. These micron particles can spread rapidly from their source to residential areas, increasing the risk of respiratory disease if exposed for long periods. The prediction system of PM2.5 propagation provides more detailed and accurate information as an early warning system to reduce health impacts on the community. According to the idea of transformative computing, the approach we propose in this paper allows computation on the dataset obtained from massive-scale PM2.5 sensor nodes via wireless sensor network. In the scheme, the deep learning model is implemented on the server nodes to extract spatiotemporal features on these datasets. This research was conducted by using dataset of air quality monitoring systems in Taiwan. This study presents a new model based on the convolutional recursive neural network to generate the prediction map. In general, the model is ...
The sparse data in PM2.5 air quality monitoring systems is frequently happened on large-scale sma... more The sparse data in PM2.5 air quality monitoring systems is frequently happened on large-scale smart city sensing applications, which is collected via massive sensors. Moreover, it could be affected by inefficient node deployment, insufficient communication, and fragmented records, which is the main challenge of the high-resolution prediction system. In addition, data privacy in the existing centralized air quality prediction system cannot be ensured because the data which are mined from end sensory nodes constantly exposed to the network. Therefore, this paper proposes a novel edge computing framework, named Federated Compressed Learning (FCL), which provides efficient data generation while ensuring data privacy for PM2.5 predictions in the application of smart city sensing. The proposed scheme inherits the basic ideas of the compression technique, regional joint learning, and considers a secure data exchange. Thus, it could reduce the data quantity while preserving data privacy. Th...
Walking has been demonstrated to improve health in people with diabetes and peripheral arterial d... more Walking has been demonstrated to improve health in people with diabetes and peripheral arterial disease. However, continuous walking can produce repeated stress on the plantar foot and cause a high risk of foot ulcers. In addition, a higher walking intensity (i.e., including different speeds and durations) will increase the risk. Therefore, quantifying the walking intensity is essential for rehabilitation interventions to indicate suitable walking exercise. This study proposed a machine learning model to classify the walking speed and duration using plantar region pressure images. A wearable plantar pressure measurement system was used to measure plantar pressures during walking. An Artificial Neural Network (ANN) was adopted to develop a model for walking intensity classification using different plantar region pressure images, including the first toe (T1), the first metatarsal head (M1), the second metatarsal head (M2), and the heel (HL). The classification consisted of three walki...
Human-centric Computing and Information Sciences, 2017
An infrared transmitting model from the observed finger vein images is proposed in this paper by ... more An infrared transmitting model from the observed finger vein images is proposed in this paper by using multi-light-intensity imaging. This model is estimated from many pixels’ values under different intensity light in the same scene. Due to the fusion method could be applied in biometric system, the vein images of finger captured in the system, we proposed in this paper, will be normalized and preserved the intact of the vein patterns of the biometric data from tested human’s body. From observed pixels under multi-light-intensity, the curve of the transmitting model is recovered by sliding both of the sampled curve segments and using curve-fitting. The fusion method with each pixel level weighting based on the proposed transmitting model curve is adopted by the smooth spatial and estimation of the block quality. Finally, the results shown that our approach is a convenient and practicable approach for the infrared image fusion and subsequent processing for biometric applications.
Recent advances in deep learning have shown many successful stories in smart healthcare applicati... more Recent advances in deep learning have shown many successful stories in smart healthcare applications with data-driven insight into improving clinical institutions’ quality of care. Excellent deep learning models are heavily data-driven. The more data trained, the more robust and more generalizable the performance of the deep learning model. However, pooling the medical data into centralized storage to train a robust deep learning model faces privacy, ownership, and strict regulation challenges. Federated learning resolves the previous challenges with a shared global deep learning model using a central aggregator server. At the same time, patient data remain with the local party, maintaining data anonymity and security. In this study, first, we provide a comprehensive, up-to-date review of research employing federated learning in healthcare applications. Second, we evaluate a set of recent challenges from a data-centric perspective in federated learning, such as data partitioning cha...
2014 Ninth International Conference on Broadband and Wireless Computing, Communication and Applications
Currently, mobile communications are provided convenient methods to explore and communicate with ... more Currently, mobile communications are provided convenient methods to explore and communicate with each other people. A multitude of services have converged on the smartphone platform, and potentially the most notable is social networking. Thus, the electronic Mobile Chat (MC) plays a very important role in the social networking. With the increasingly growing reliance on Mobile Chat System (MCS) in one hand, and the growing number of vulnerabilities and attacks on the other hand, there is an increasingly demand for the security solutions. Despite of the critical role of MCS in the typical Internet mobile user's life, electronic MC services are not so secure. Therefore, the secure End-to-End Mobile Chat (SE2E-MC) scheme is proposed to be one of the suitable solutions. The basic framework for SE2E-MC scheme and its associated requirements are also designed in this paper. The proposal is implemented to provide mutual authentication and prevent the password guessing attack and the undetectable on-line password guessing attack. Finally, the scheme is a password-based authentication and key agreement (AKA) having easy remembered property.
Software defined network (SDN) technology provides potential solutions for the 5G mobile communic... more Software defined network (SDN) technology provides potential solutions for the 5G mobile communication systems. Vehicle-to-vehicle (V2V) communications are the main topology of the Intelligent Transportation System (ITS). Its performance requirement of low latency is one of the most challenging issues. In this study, the transmission latency of V2V communications in software defined vehicular networks (SDVN) is investigated. To minimize the transmission latency in SDVNs, this work proposed five multi-hop routing connection strategies. Simulation results show that under the vehicle density 0.1 ≤ ρ ≤ 0.33, the proposed furthest vehicle (FV) routing algorithm can perform the lowest average transmission latency in SDVNs.
Journal of Electronic Science and Technology, 2019
A peer-to-peer (P2P) multimedia conferencing service is operating that users share their resource... more A peer-to-peer (P2P) multimedia conferencing service is operating that users share their resources to each other on the Internet. It can solve the problem in the centralized conferencing architecture, such as the centralized loading, single point error, and expensive infrastructure. However, P2P networks have the problem that a peer has a difference between the physical location and logical location in the overlay network. In the viewpoint of P2P networks, the nearest conference resource may be far away geographically. The P2P-session initiation protocol (P2P-SIP) multimedia conference is to construct an application-based logical multicast network efficiently according to physical network information. Thus, this paper proposes a real-time streaming relay mechanism for P2P conferences on hierarchical overlay networks. The real-time streaming relay mechanism can improve the transportation efficiency of conferencing stream exchange well based on the application-layer multicast (ALM) st...
Insider threat has attracted considerable attention in security industry. It is difficult to dete... more Insider threat has attracted considerable attention in security industry. It is difficult to detect insiders, because they know organization’s security countermeasures and usually hide their tracks in their normal activities. For evaluating insider detection algorithm on specific organization, it is important to generate a test suite with the corresponding normal activities. However, it is costly and time consuming to generate tailor-made test suite. Due to the complexity of combining different insider attack technique with different organization’s audit data, the insider attack scenario modeling issue arises when adaptively generate test suite for insider threat detection. In this paper, we propose the insider attack frame hierarchy to describe stereotype features of insider attack scenario. The proposed frame-based approach has been combined with the RBAC technologies, and its instantiation property allow us generate the customized insider attack test suite with full test coverage...
Blockchain technology is growing very rapidly, not only in the field of cryptocurrency transactio... more Blockchain technology is growing very rapidly, not only in the field of cryptocurrency transactions but also in other fields such as health care services, service companies, manufacturing. Smart contracts are a series of instruction codes, which automatically verify, execute, and tamper with. With the integration of blockchain technology, it can perform tasks in real time with a high level of security. In this study, we built a smart contract model based on online haggling in determining the purchase of a product. Buyers and sellers haggle with each other for the products they want via online the seller web app. Finally, we propose a smart contract design model using online haggling, which can help provide decision-making in determining the appropriate price from the seller and buyer agreement.
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Papers by Hsing-Chung Chen