Browsing by Author "Lo, Chi-Chun"

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A Cloud-Based Recommender System - A Case Study of Delicacy Recommendation
(2011)
Chen, Chi-Hua
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Yang, Ya-Ching
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Shih, Pei-Liang
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Lee, Fang-Yi
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Lo, Chi-Chun
Delicacy recommendation services are the trend of the future. In this paper, we propose an effective decision support systems (DSS), the Cloud-Based Recommender System (CBRS), which provides the introduction and commentaries of delicacies and restaurants with relevant recommendation. CBRS provides the web content retrieval agent (WCRA) and multiple document summarization (MDS) technology to generate summary of commentaries. Finally, CBRS combines with the cloud computing for MDS to provide delicacy recommendation services. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]
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 Flexible Access Control Mechanism for Mobile Commerce
(2011)
Lo, Chi-Chun
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Huang, Chun-Chieh
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Chang, Chung-Huan
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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
In this paper, we propose a flexible access control mechanism, which integrates domain information and confidence values, for mobile commerce. When user requests an access to the data server, the data server fetches and returns results according to the user's access right. Algorithms demonstrate the flexible access control is effective and flexible.
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 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 green positioning algorithm for Campus Guidance System
(2012)
Chen, Chi-Hua
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Lin, Bon-Yeh
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Lin, Chun-Hao
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Liu, Yen-Szu
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Lo, Chi-Chun
In this paper, we propose a new CGS, called the Green Campus Guidance System (GCGS). The GCGS employs the Fingerprint Position Algorithm (FPA) using Received Signal Strength (RSS) from mobile stations/user equipment through cellular networks and Location-Based Services (LBSs) for user reference. In experiments, the results show that the error of location estimation using FPA is about 9.92 m. As to power consumption, the cost per sample of GPS is 27.68 times of that of FPA. Consequently, the FPA exerts itself as a green positioning algorithm, and thus can be used to support GCGS.
A hybrid information security risk assessment procedure considering interdependences between controls
(2012-01-01)
Lo, Chi-Chun
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Chen, Wan-Jia
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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
Risk assessment is the core process of information security risk management. Organizations use risk assessment to determine the risks within an information system and provide sufficient means to reduce these risks. In this paper, a hybrid procedure for evaluating risk levels of information security under various security controls is proposed. First, this procedure applies the Decision Making Trial and Evaluation Laboratory (DEMATEL) approach to construct interrelations among security control areas. Secondly, likelihood ratings are obtained through the Analytic Network Process (ANP) method: as a result, the proposed procedure can detect the interdependences and feedback between security control families and function in real world situations. Lastly, the Fuzzy Linguistic Quantifiers-guided Maximum Entropy Order-Weighted averaging (FLQ-MEOWA) operator is used to aggregate impact values assessed by experts, applied to diminish the influence of extreme evaluations such as personal views and drastic perspectives. A real world application in a branch office of the health insurance institute in Taiwan was examined to verify the proposed procedure. By analyzing the acquired data, we confirm the proposed procedure certainly detects the influential factors among security control areas. This procedure also evaluates risk levels more accurately by coping with the interdependencies among security control families and determines the information systems safeguards required for better security, therefore enabling organizations to accomplish their missions. Crown Copyright (C) 2011 Published by Elsevier Ltd. All rights reserved.
A Network Behavior Analysis System for Cloud Computing Service
(2011-03-01)
Lin, Bon-Yeh
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Chen, Chi-Hua
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Chang, Hsu-Chia
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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
It will be full of distributed network services and a large quantity of data in network environment. It is important to dynamically retrieve the real-time network information when the information is published in network. In the determination of Optimal Cycle for Network Information Retrieval (OCNIR), the network loading and the cost of information retrieval are higher when the retrieval frequency is higher. If the retrieval frequency is too low, the delay time of information is long. For this reasoning, the OCNIR is an important issue. However, the OCNIR for cloud computing service has not been investigated. In this paper, we provide the integration of web service techniques and Network Behavior Analysis Model (NBAM). We implement Service-Oriented Architecture (SOA) environment with Semantic Web (SW) and NBAM to accomplish a Network Behavior Analyis System (NBAS) for cloud computing service. The major contents of this research are follows: (1) the establishment of NBAM, (2) the determination of the optimal cycle for network information retrieval, and (3) the establishment of data transmission and analysis based on SOA. We develop the approach and implement the NBAS for individuals or enterprises to find out NBAM and OCNIR, test this approach in a domain with real-time data alteration, and then evaluate this approach.
A Novel Real-Time Speech Summarizer System for the Learning of Sustainability
(2015-04-01)
Wang, Hsiu-Wen
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Cheng, Ding-Yuan
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Chen, Chi-Hua
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Wu, Yu-Rou
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Lo, Chi-Chun
As the number of speech and video documents increases on the Internet and portable devices proliferate, speech summarization becomes increasingly essential. Relevant research in this domain has typically focused on broadcasts and news; however, the automatic summarization methods used in the past may not apply to other speech domains (e.g., speech in lectures). Therefore, this study explores the lecture speech domain. The features used in previous research were analyzed and suitable features were selected following experimentation; subsequently, a three-phase real-time speech summarizer for the learning of sustainability (RTSSLS) was proposed. Phase One involved selecting independent features (e.g., centrality, resemblance to the title, sentence length, term frequency, and thematic words) and calculating the independent feature scores; Phase Two involved calculating the dependent features, such as the position compared with the independent feature scores; and Phase Three involved comparing these feature scores to obtain weighted averages of the function-scores, determine the highest-scoring sentence, and provide a summary. In practical results, the accuracies of macro-average and micro-average for the RTSSLS were 70% and 73%, respectively. Therefore, using a RTSSLS can enable users to acquire key speech information for the learning of sustainability.
A Novel Speed Estimation Method Using Location Service Events Based on Fingerprint Positioning
(2011-11-01)
Lin, Bon-Yeh
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Chen, Chi-Hua
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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
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Department of Information Management and Finance
The rise of economic growth and technology advance has led to improve the quality of traditional transport system. Intelligent Transportation System (ITS) has become more and more popular. The building and promotion of real-time traffic information system is an important part of ITS. The traffic information estimations from cellular network data are more immediately, cost-effective, and easy to deploy and maintain than traditional methods. In this paper, we propose a novel speed estimation method using Location Service (LCS) events based on Fingerprint Positioning Algorithm (FPA). In experiments, we compare the estimated positioning information and speed information with the real information obtained from Global Position System (GPS) receiver. The results show that the average errors of location determination by using FPA and the traditional cell ID based location method are 36.11 meters and 714.07 meters, respectively. For speed estimation, the average error ratio of speed estimation by using FPA and the traditional cell ID based location method are 3.39% and 85.32%, respectively. Therefore, using FPA provides better accuracies of location determination and speed estimation than using cell ID based location method defined in the LCS specification. This approach is feasible to estimate traffic information for ITS improvement.
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
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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 Real-time Campus Guidance System Based on Energy Efficient Location Determination Method
(2011)
Lin, Chun-Hao
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Liu, Yen-Szu
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Chen, Chi-Hua
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Lin, Bon-Yeh
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Lo, Chi-Chun
Recently guidance system is becoming more popular, as more people realize its benefits. There have been many developments on campus guidance system (CGS) in personal digital assistant (PDA) and smart phone. The building and promotion of the energy efficient location determination method is an important part of CGS. The cellular-based location determination using RSS from cellular network is more immediately, power-effective, and easy to deploy and maintain than traditional methods. In this paper, we design the CGS which provides the fingerprint position algorithm (FPA) using RSS from cellular networks and location-based service (LBS) for user reference. In experiments, we compare the estimated positioning information with the real information from global position system (GPS) receiver. The results show that the error of location estimation using FPA is about 9.92 meters. This approach is feasible to be applied to CGS.
A Real-time Crime Detection System Based on Lawful Interception - A Case Study of MSN Messenger
(2011)
Chen, Chi-Hua
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Chen, Wan-Jia
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Wang, Ya-Fen
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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
In recent years, the number of online crimes (e. g., the various emerging scams and criminal schemes) has increased. Online crime suspects utilize the anonymous nature of web to disguise their identity through various methods and evade detection and surveillance from law enforcement agencies. This study proposes an effective lawful interception system, Real-time Crime Detection System (RCDS), which includes Criminal Investigation Bureau (CIB), Internet Service Providers (ISP), and Network Interception Server (NIS) to establish a legally sanctioned lawful interception process which can collect and store evidence for criminal detection in real time. We provide a case study of MSN Messenger to describe the MSN Protocol (MSNP), information flow process, and lawful interception methodologies. The RCDS can provide criminal detection and surveillance services for MSN to obtain criminal communication records in turn reducing online criminal activities. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]
A Real-Time Pothole Detection Approach for Intelligent Transportation System
(2015-01-01)
Wang, Hsiu-Wen
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Chen, Chi-Hua
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Cheng, Ding-Yuan
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Lin, Chun-Hao
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Lo, Chi-Chun
In recent years, fast economic growth and rapid technology advance have led to significant impact on the quality of traditional transport system. Intelligent transportation system(ITS), which aims to improve the transport system, has become more and more popular. Furthermore, improving the safety of traffic is an important issue of ITS, and the pothole on the road causes serious harm to drivers' safety. Therefore, drivers' safety may be improved with the establishment of real-time pothole detection system for sharing the pothole information. Moreover, using the mobile device to detect potholes has been more popular in recent years. This approach can detect potholes with lower cost in a comprehensive environment. This study proposes a pothole detection method based on the mobile sensing. The accelerometer data is normalized by Euler angle computation and is adopted in the pothole detection algorithm to obtain the pothole information. Moreover, the spatial interpolation method is used to reduce the location errors from global positioning system (GPS) data. In experiments, the results show that the proposed approach can precisely detect potholes without false-positives, and the higher accuracy is performed by the proposed approach. Therefore, the proposed real-time pothole detection approach can be used to improve the safety of traffic for ITS.
A Real-time Traffic Information Model Using GPS-based Probe Car Data
(2011)
Chen, Wan-Jia
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Chen, Chi-Hua
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Lin, Bon-Yeh
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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
In recent year, the rise of economic growth and technology advance leads to improve the quality of service of traditional transport system. Intelligent Transportation System (ITS) has become more and more popular. At present, the collection of real-time traffic information is executed in two ways: (1) Stationary Vehicle Detectors (VD) and (2) Global Position System (GPS)-based probe cars reporting. However, VD devices need a large sum of money to build and maintain. Therefore, we propose the linear regression model to infer the equation between vehicle speed and traffic flow. The traffic flow can be estimated from the speed which is obtained from GPS-based probe cars. In experiments, the Speed Error Ratio (SER) and Flow Error Ratio (FER) of linear regression model are 4.60% and 24.63% respectively. The estimated speed and traffic flow by using linear regression model is better than by using linear model, power law model, exponential model, and normal distribution model. Therefore, the linear regression model can be used to estimate traffic information for ITS.
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.