Browsing by Author "Chao, Kuo-Ming"

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A Cost-Effective Planning Graph Approach for Large-Scale Web Service Composition
(2012)
Lin, Szu-Yin
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Lin, Guan-Ting
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Chao, Kuo-Ming
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Lo, Chi-Chun
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資訊管理與財務金融系註：原資管所+財金所
Web Service Composition (WSC) problems can be considered as a service matching problem, which means that the output parameters of a Web service can be used as inputs of another one. However, when a very large number of Web services are deployed in the environment, the service composition has become sophisticated and complicated process. In this study, we proposed a novel cost-effective Web service composition mechanism. It utilizes planning graph based on backward search algorithm to find multiple feasible solutions and recommends a best composition solution according to the lowest service cost. In other words, the proposed approach is a goal-driven mechanism, which can recommend the approximate solutions, but it consumes fewer amounts of Web services and less nested levels of composite service. Finally, we implement a simulation platform to validate the proposed cost-effective planning graph mechanism in large-scale Web services environment. The simulation results show that our proposed algorithm based on the backward planning graph has reduced by 94% service cost in three different environments of service composition that is compared with other existing service composition approaches which are based on a forward planning graph.
A Cross-age Face Recognition Approach Using Fog Computing Architecture for User Authentication on Mobile Devices
(2018-01-01)
Lin, Wen-Hui
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Wang, Ping
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Wu, Bao-Hua
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Chao, Kuo-Ming
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Lo, Chi-Chun
Mobile commerce security needs quality services where mobile devices respond in real-time and traditional cloud computing approach uses a centralized architecture does not support these systems with such time dependency well. Thus, this study proposes a cross-age face-recognition model with MobileNets to determine the identity of a user in the situation of aging appearance change on a fog computing architecture. Especially, this study uses a face-recognition technique based on a distributed concept. In this concept, MobileNet-based face recognition system effectively performs cross-age face recognition for identity authentication with the enhanced facial features of the users locally. Overall, the MobileNet model reaches acceptable prediction accuracy with lower latency in face recognition process compared with that of the existing CNNs schemes.
A Face-Recognition Approach Using Deep Reinforcement Learning Approach for User Authentication
(2017-01-01)
Wang, Ping
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Lin, Wen-Hui
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Chao, Kuo-Ming
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Lo, Chi-Chun
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資訊管理與財務金融系註：原資管所+財金所
Numerous crime-related security concerns exist in e-commerce transactions recently. User authentication for mobile payment has numerous approaches including face recognition, iris scan, and fingerprint scan to identify user's true identity by comparing the biometric features of users with patterns in the signature database. Existing studies on the face recognition problem focus mainly on the static analysis to determine the face recognition precision by examining the facial features of images with different facial expressions for users rather than the dynamic aspects where images were are often vague affected by lighting changes with different poses. Because the lighting, facial expressions, and facial details varied in the face recognition process. Consequently, it limits the effectiveness of scheme with which to determine the true identity. Accordingly, this study focused on a face recognition process under the situation of vague facial features using deep reinforcement learning (DRL) approach with convolutional neuron networks (CNNs) thru facial feature extraction, transformation, and comparison to determine the user identity for mobile payment. Specifically, the proposed authentication scheme uses back propagation algorithm to effectively improve the accuracy of face recognition using feed-forward network architecture for CNNs. Overall, the proposed scheme provided a higher precision of face recognition (100% at gamma correction gamma located in [0.5, 1.6]) compared with the average precision for face image (approximately 99.5% at normal lighting gamma = 1) of the existing CNN schemes with ImageNet 2012 Challenge training data set.
A fuzzy decision model of risk assessment through fuzzy preference relations with users\' confidence-interval
(2006)
Wang, Ping
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Chao, Kuo-Ming
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Huang, Chun-Lung
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Lo, Chi-Chun
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Hu, Chia-Ling
Risk assessment for security management is a complex process which linked to substantial ambiguous However existing techniques of risk analysis determine the solution by the probability distribution function of threats and its impact loss In fact, it is difficult for users to collect precise and adequate events to estimate the Probability of threats and impact losses. Consequently, a fuzzy risk analysis model is developed to prioritize the risk ranking of assets. The proposed model uses Pseudo-Order Preference Model (POPM) to represent the imprecise preference degree of decision maker and determine the ranking of alternative using fuzzy majority concept It extends the traditional risk analysis using fuzzy multiple person decision making (MPDM) theory and POPM to risk analysis in fuzzy environment Finally, a real case of risk assessment for the Internet Data Center (IDC) is given to ifiustrate our approach.
A fuzzy group-preferences analysis method for new-product development
(2006-11-01)
Lo, Chin-Chun
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Wang, Ping
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Chao, Kuo-Ming
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資訊管理與財務金融系註：原資管所+財金所
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Department of Information Management and Finance
This paper reports a new idea-screening method for new product development (NPD) with a group of decision makers having imprecise, inconsistent and uncertain preferences. The traditional NPD analysis method determines the solution using the membership function of fuzzy sets which cannot treat negative evidence. The advantage of vague sets, with the capability of representing negative evidence, is that they support the decision makers with the ability of modeling uncertain opinions. In this paper, we present a new method for new-product screening in the NPD process by relaxing a number of assumptions so that imprecise, inconsistent and uncertain ratings can be considered. In addition, a new similarity measure for vague sets is introduced to produce a ratings aggregation for a group of decision makers. Numerical illustrations show that the proposed model can outperform conventional fuzzy methods. It is able to provide decision makers (DMs) with consistent information and to model situations where vague and ill-defined information exist in the decision process. (c) 2006 Elsevier Ltd. All rights reserved.
A fuzzy model for selection of QoS-aware web services
(2006)
Wang, Ping
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Chao, Kuo-Ming
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Lo, Chi-Chun
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Huang, Chun-Lung
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Li, Yinsheng
With the increasing popularity of employing web services, quality of service (QoS) measure of service becomes a significant concern for service consumers and providers. However, current technologies are poor to identify the relative importance of non-functional QoS criteria for web services and they are not fitting well for selecting the appropriate service. In this paper, a new scheme for right selection of QoS-aware of web services which exploits fuzzy logic to locate and select the right service based on customer\'s preference or sath faction degree. The aim is to compute both finctional and non-functional weightings of QoS criteria and to assist customers to make the right choice.for web services.
A fuzzy outranking approach in risk analysis of web service security
(2007-03-01)
Wang, Ping
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Chao, Kuo-Ming
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Lo, Chi-Chun
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Huang, Chun-Lung
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Younas, Muhammad
Risk analysis is considered as an important process to identify the known and potential vulnerabilities and threats in the web services security. It is quite difficult for users to collect adequate events to estimate the full vulnerabilities and probability of threats in the Web, due to the rapid change of the malicious attacks and the new computers vulnerabilities. In this paper, a fuzzy risk assessment model is developed in order to evaluate the risk of web services in a situation where complete information is not available. The proposed model extends Pseudo-Order Preference Model (POPM) to estimate the imprecise risk based on richness of information and to determine their ranking using a weighted additive rule. A case Study of a number of web services is presented in order to test the proposed approach.
A Novel Threat and Risk Assessment Mechanism for Security Controls in Service Management
(2013)
Wang, Ping
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Chao, Kuo-Ming
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Lo, Chi-Chun
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Most existing Threat and Risk Assessment (TRA) schemes for cloud services use a converse thinking approach to develop theoretical solutions for minimizing the risk of security breeches at a minimal cost. However, to support rational management decisions, TRA schemes require a careful analysis of the trade-off between the residual risk and the Return on Investment (ROI) given prescribed budget and time constraints. Accordingly, the present study proposes an improved Attack-Defense Tree mechanism designated as iADTree, for solving the TRA problem in cloud computing environments. The proposed scheme enables defenders to identify appropriate countermeasures in accordance with three different defensive strategies associated with the organization\'s security policy. In implementing the proposed scheme, a sandbox technique is used to examine the attack profile and attack probability of various forms of cyber attacks. The cost and residual risk of various defensive strategies are then evaluated and presented to the defender as a set of recommendations. Defense evaluation metrics for each node for probabilistic analysis is used to simulate the attack results. The simulations focus specifically on the attack profile of botnet to the threat risk assessment. The validity of the proposed approach is demonstrated by simulating the TRA process for a Zeus botnet attack. Overall, the results show that iADTree provides an effective means of modeling the interaction process between the attacker and the defender, analyzing the risk at each node of the tree given various defensive strategies, and developing cost-effective countermeasures for mitigating the network threat.
A reputation-based computing approach in trusted web service provisions
(2015-07-01)
Wang, Ping
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Chao, Kuo-Ming
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Lo, Chi-Chun
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Some service reputation approaches primarily consider the consumer\'s prior experience of the service via opinion feedback system, may neglect the effect of TrustTransition (TT) in the recommendations of others. The service reputation is propagated via referral network recommendations for service composition and eventually builds a distinct level of consumer trust in the service. Accordingly, the present study proposes a service selection model in which the reputation of a service provider is estimated by collecting consumer feedbacks and other\'s recommendations in open networks. The degree of service reputation is appropriately estimated using fuzzy Petri net (FPN) to model the referral activities across the social networks and outrank a set of service alternatives using the global reputation score of a service. Two examples of social services selection are used to demonstrate the proposed approach. The proposed model effectively solves the trust transition problem in the indirect recommendation of the service selection and also enables deception detection in terms of existing evidences for assessment of evaluator credibility that excludes the false evidences of dishonest evaluators.
A Social Trust based Recommendation Mechanism for Web Service Dynamic Collaboration
(2013)
Lin, Szu-Yin
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Yang, Ya-Ching
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Lo, Chi-Chun
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Chao, Kuo-Ming
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資訊管理與財務金融系註：原資管所+財金所
In the distributed commercial environment, many enterprises utilize Web services to provide their resources such as data and applications to consumers. They collaborate with other relevant enterprises to accomplish tasks by sharing processes and resources. However, it is difficult to find the appropriate web service combination for enterprise, because the Quality of Services (QoS) that are widely used to select Web services is not sufficient anymore. In dynamic collaboration environment, it does not only need to consider the QoS, functionality and degree of matching, but also the social trust relationship between enterprises. This study proposes a social-trust-based recommendation mechanism for service-oriented dynamic collaboration. It uses the legal binding of Service Level Agreement and the characteristics of Social Trust Network of Web services to recommend proper and trustworthy services to support dynamic collaboration.
A study on representation of QoS in UDDI for web services composition
(2008)
Lo, Chi-Chun
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Cheng, Ding-Yuan
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Lin, Ping-Chi
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Chao, Kuo-Ming
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資訊管理與財務金融系註：原資管所+財金所
With the increasing popularity of deploying web services, quality of service (QoS) becomes a significant concern for service consumers and providers for service selection. However representing and storing the values of QoS attributes are problematic, as the current Universal Description, Discovery and Integration (UDDI) was not designed to accommodate these emerging requirements. To solve the problems of storing QoS in UDDI and aggregating QoS values, three different approaches, namely type, keyword based and ontological approaches to model QoS tModel (Technical Model) have been proposed. The aim is to study these approaches and other existing QoS tModel representation for their efficiency and consistency in service selection. In this paper we also report a number of experimental results based on an example in order to evaluate these approaches.
A user centric service-oriented modeling approach
(2011-07-01)
Cheng, Ding-Yuan
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Chao, Kuo-Ming
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Lo, Chi-Chun
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Tsai, Chen-Fang
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資訊管理與財務金融系註：原資管所+財金所
With rapid development of service-oriented architecture and cloud computing, web services have been widely employed on the Internet. Quality of Service (QoS) is a very important criterion for service consumers to measure and select services. The selection of web services with respect to non-functional QoS criteria can be considered as a Multiple Criteria Decision Making (MCDM) problem when multiple consumers need to share a number of services. This paper describes a new user centric service-oriented modeling approach which is featured by integrating fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Service Component Architecture (SCA) to facilitate web service selection and composition and to effectively satisfy a group of service consumers' subjective requirements and preferences in the dynamic environment. The main contribution of this method is able to translate a group of users' fuzzy requirements to services as well as model different levels of hardware and software as services to meet the requirements. We also design a simulated environment that includes 8*8 LED matrix on a circuit board that corresponds to an office with different appliances to demonstrate the dynamic service selection and binding. The simulation is used to assess the computational efficiency of the fuzzy TOPSIS method and the effectiveness of the proposed system.
An Efficient Flow Control Approach for SDN-based Network Threat Detection and Migration Using Support Vector Machine
(2016)
Wang, Ping
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Lin, Hsiao-Chung
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Lin, Wen-Hui
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Chao, Kuo-Ming
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Lo, Chi-Chun
Most existing approaches for solving the network threat problems focus on the specific security mechanisms, for example, network intrusion detection system (NIDS) detection, firewall configuration, rather than on flow management approaches to defend network threats with an SDN (Software Defined Networking) architecture. Accordingly, this study proposes an improved behaviour-based SVM (support vector machine) with learning algorithm for use in the security monitoring system (SMS) to categorize network threats for network intrusion detection system. The model also adopted the ID3 decision tree theory to outrank raw features and determine the most qualified features to train support vector classifier (SVC) considering the overall detection precision rate of experiments which speeds up the learning of normal and intrusive patterns and and increases the accuracy of detecting intrusion. By using sFlow collector and analyzer associated with sFlow-RT toolset, the experimental results proved that the SMS enables a defender to classify the network threats with defence strategies and defend network threats.
An efficient transaction commit protocol for composite web services
(2006)
Younas, Muhammad
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Chao, Kuo-Ming
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Lo, Chi-Chun
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Li, Yinsheng
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資訊管理與財務金融系註：原資管所+財金所
Transaction commit protocols have widely been used to ensure the correctness and reliability of distributed applications. This paper investigates into the performance of such protocols within the context of composite web services. It presents a new commit protocol which aims to improve the performance of composite web services transactions. The proposed protocol is tested through various analytical experiments. These experiments reveal that the proposed protocol significantly improves the performance in committing a composite web service transaction. The experiments also exhibit the processing overhead of the proposed protocol in the case of unsuccessful execution of a web service transaction.
Consumer-centric QoS-aware selection of web services
(2008-03-01)
Lin, Wei-Li
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Lo, Chi-Chun
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Chao, Kuo-Ming
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Younas, Muhammad
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資訊管理與財務金融系註：原資管所+財金所
There exist many web services which exhibit similar functional characteristics. It is imperative to provide service consumers with facilities for selecting required web services according to their non-functional characteristics or quality of service (QoS). However, the selection process is greatly complicated by the distinct views of service providers and consumers on the services QoS. For instance, they may have distinct views of the service reliability-wherein a consumer considers that a service is reliable if its success rate is higher than 99%, while a provider may consider its service as reliable if its success rate is higher than 90%. The aim of this paper is to resolve such conflicts and to ensure consensus on the QoS characteristics in the selection of web services. It proposes a QoS Consensus Moderation Approach (QCMA) in order to perform QoS consensus and to alleviate the differences on QoS characteristics in the selection of web services. The proposed approach is implemented as a prototype tool and is tested on a case study of a hotel booking web service. Experimental results show that the proposed approach greatly improves the service selection process in a dynamic and uncertain environment of web services. (c) 2007 Elsevier Inc. All rights reserved.
Dynamic fine-tuning stacked auto-encoder neural network for weather forecast
(2018-12-01)
Lin, Szu-Yin
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Chiang, Chi-Chun
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Li, Jung-Bin
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Hung, Zih-Siang
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Chao, Kuo-Ming
With the advent of the big data era, dynamic and real-time data have increased in both volume and variety. It is difficult to make accurate predictions regarding data as they undergo rapid and dynamic changes. Autonomous cloud computing aims to reduce the time required for traditional machine learning. The stacked auto-encoder is a neural network approach in machine learning for feature extraction. It attempts to model high-level abstractions and to reduce data dimensions by using multiple processing layers. However, some common issues may occur during the implementation of deep learning or neural network models, such as over-complicated dimensions of the input data and difficulty in processing dynamic data. Therefore, combining the concept of dynamic data-driven system with a stacked auto-encoder neural network will help obtain the dynamic data correlation or relationship between the prediction results and actual data in a dynamic environment. This study applies the concept of a dynamic data-driven system to obtain the correlations between the prediction goals and number of different combination results. Association analysis, sequence analysis, and stacked auto-encoder neural network are employed to design a dynamic data-driven system based on deep learning. (C) 2018 Elsevier B.V. All rights reserved.
Fuzzy consensus on QoS in web services discovery
(2006)
Lin, Wei-Li
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Lo, Chi-Chun
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Chao, Kuo-Ming
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Younas, Muhammad
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資訊管理與財務金融系註：原資管所+財金所
Ensuring consensus on QoS attributes is imperative for the discovery of web services. Inconsistent views of service providers and consumers on QoS attributes could be problematic, even though they have consensus on characteristics. For instance, they may have distinct views of the QoS attribute of service reliability, wherein a consumer considers that a service is reliable if its success rate is 99.9% or 100016, while providers may consider its service as reliable if its success rate is higher than 90% Different expectations in service discovery could hinder prevailing of the web services. This paper proposes a QoS Consensus Moderation Approach (QCMA) in order to perform QoS consensus and to alleviate the differences on QoS requirements in the web services discovery. The proposed approach is implemented and evaluated through an example of hotel booking web service.
Fuzzy Similarity Clustering for Consumer-Centric QoS-aware Selection of Web Services
(2009)
Lin, Wei-Li
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Lo, Chi-Chun
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Chao, Kuo-Ming
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Godwin, Nick
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資訊管理與財務金融系註：原資管所+財金所
Appropriate use of group consensus on service consumers' QoS opinions can improve web service discovery. For web service participants with different backgrounds or preferences it may not be easy to reach a consensus on the Web service QoS opinions, so they should be treated as multi-groups. Also, to prevent possibly useful opinions from being omitted unintentionally, fuzzy clustering criteria for the "multi-groups" framework should be adopted. In this paper we have proposed a FMGSAM (Fuzzy Multi-Groups based SAM) to improve the accuracy in group opinion similarity analysis and the efficiency in generating group consensus.
Information Management and Applications of Intelligent Transportation System
(2015-01-01)
Lo, Chi-Chun
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Chao, Kuo-Ming
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Kung, Hsu-Yang
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Chen, Chi-Hua
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Chang, Maiga
Integrating Semantic Web and Object-Oriented Programming for Cooperative Design
(2009)
Chiu, Po-Huan
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Lo, Chi-Chun
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Chao, Kuo-Ming
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資訊管理與財務金融系註：原資管所+財金所
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Department of Information Management and Finance
Object-oriented programming (OOP) is a mainstream paradigm for engineering design software tool development. An emerging requirement is the introduction of semantics to achieve heterogeneous information sharing, but many challenges exist. Examples include using object methods to manipulate an RDF data, automatically converting data into RDF format, and supporting various programming languages. In addition, limitations to description capabilities for relationships among object-oriented classes exceed those of RDF, thus hindering direct mapping between object-oriented and Semantic Web classes. Our proposed semantic object framework (SOF) combines object-oriented design and Semantic Web features. SOF utilizes embedded comments in source code to describe semantic relationships between classes and attributes. We use a mobile phone design case study to illustrate how the proposed system operates.