Browsing by Author "Wang, Ping"

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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
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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 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
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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.
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.
DEEP REINFORCEMENT LEARNING FOR MOBILE 5G AND BEYOND Fundamentals, Applications, and Challenges
(2019-06-01)
Xiong, Zehui
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Zhang, Yang
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Niyato, Dusit
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Deng, Ruilong
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Wang, Ping
On optimal decision for QoS-aware composite service selection
(2010-01-01)
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
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Department of Information Management and Finance
The increasing popularity of employing web services for distributed systems contributes to the significance of service discovery. However, duplicated and similar functional features existing among services require service consumers to include additional aspects to evaluate the services. Generally, the service consumers would have different view on the quality of service (QoS) of service attributes. How to select the best composite service in theory among available service (WS) candidates for consumers is an interesting practical issue. This work proposes a QoS-aware service selection model based on fuzzy linear programming (FLP) technologies, in order to identify their dissimilarity on service alternatives. assist service consumers in selecting most suitable services with consideration of their expectations and preferences. This approach can obtain the optimal solution of consensual weight of QoS attribute and fuzzy positive ideal solution (FPIS) by extending LINMAP method, developed by Srinivasan and Shocker. Finally, two numerical examples are given to demonstrate the process of QoS-aware web service selection. The experimental results demonstrated that it is a feasible and supplementary manner in selecting the of web services. (C) 2009 Elsevier Ltd. All rights reserved.
QoS-aware mobile service transactions in a wireless environment
(2007-06-10)
Younas, Muhammad
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Chao, Kuo-Ming
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Wang, Ping
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Huang, Chun-Lung
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資訊管理與財務金融系註：原資管所+財金所
Mobile computing greatly facilitates the provision of mobile services using portable and handheld devices which are connected through wireless networks. A pre-requisite for the provision of an effective service is to ensure quality of service (QoS) during the concurrent execution of requests and system or network failures. This paper presents a new transaction management approach for the provision of mobile services which is based on advanced transaction models and fuzzy selection criteria. It employs a novel QoS consensus moderation approach in order to select preferred mobile services from among various alternatives, thus providing multiple pathways to the completion of mobile service transactions. Unlike traditional transaction management schemes, the proposed approach takes into account QoS attributes in the commit process of mobile service transactions. The proposed approach is implemented as a prototype tool and evaluated through a number of experiments. Experimental results show that the proposed approach effectively selects mobile services and significantly increases the throughput (i.e. commit rate) of mobile service transactions. Copyright (C) 2007 John Wiley & Sons, Ltd.
Satisfaction-based Web service discovery and selection scheme utilizing vague sets theory
(2015-08-01)
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
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Department of Information Management and Finance
Most existing QoS-aware Service Discovery and Selection (QSDS) schemes use linguistic terms to describe the QoS satisfaction degree when ranking competing alternatives. However, such schemes determine the degree of QoS satisfaction using fuzzy set membership functions, and cannot therefore take negative evidence (i.e., consumer dissatisfaction) into account. By contrast, vague sets provide the ability to represent both positive and negative evidence when modeling uncertain objects. Accordingly, the present study proposes a new satisfaction-based Web service ranking method for QSDS problems involving a group of online service consumers with imprecise and inconsistent expectations and degrees of satisfaction regarding multiple QoS criteria. Importantly, the proposed approach overcomes the uncertainty regarding the difference between the users\' expectations and their degree of satisfaction inherent in Dempster-Shafer (D-S) evidence theory. Overall, the results show that the proposed scheme provides an effective means of solving the problem of vague and ill-defined information in the QSDS decision-making process.
Service discovery through consensus-based preferences
(2006-07-01)
Huang, Chun-Lung
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Chao, Kuo-Ming
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Lo, Chi-Chun
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Wang, Ping
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Chung, Jen-Yao
The prevailing research trend is to discover and compose web services dynamically in order to develop composite services that provide enhanced functionality. Most existing discovery techniques do not take into account the diverse preferences and expectations of service consumers. For instance, searching for a web service (for cheap and convenient flights), does not involve only functional requirements, but it also includes subjective and fuzzy opinions in query terms such as "cheap and convenient". Different perceptions of such terms by service consumers and providers create serious problems in service discovery. This is compounded by the fact that they may have different preferences or opinions. This paper presents a new service discovery approach to model subjective and fuzzy opinions, and to assist them in reaching a consensus. The method achieves a common consensus on the distinct opinions and expectations of individual users. This process is iterative and additional fuzzy preferences can be included to improve precision rate in web service discovery.
The rural carbonaceous aerosols in coarse, fine, and ultrafine particles during haze pollution in northwestern China
(2016-03)
Zhu, Chong-Shu
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Cao, Jun-Ji
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Tsai, Chuen-Jinn
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Shen, Zhen-Xing
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Liu, Sui-Xin
The carbonaceous aerosol concentrations in coarse particle (PM10: Dp <= 10 mu m, particulate matter with an aerodynamic diameter less than 10 mu m), fine particle (PM2.5: Dp <= 2.5 mu m), and ultrafine particle (PM0.133: Dp <= 0.113 mu m) carbon fractions in a rural area were investigated during haze events in northwestern China. The results indicated that PM2.5 contributed a large fraction in PM10. OC (organic carbon) accounted for 33, 41, and 62 % of PM10, PM2.5, and PM0.133, and those were 2, 2.4, and 0.4 % for EC (elemental carbon) in a rural area, respectively. OC3 was more abundant than other organic carbon fractions in three PMs, and char dominated EC in PM10 and PM2.5 while soot dominated EC in PM0.133. The present study inferred that K+, OP, and OC3 are good biomass burning tracers for rural PM10 and PM2.5, but not for PM0.133 during haze pollution. Our results suggest that biomass burning is likely to be an important contributor to rural PMs in northwestern China. It is necessary to establish biomass burning control policies for the mitigation of severe haze pollution in a rural area.
Using Dynamic Taint Approach for of Malware Threat
(2015)
Wang, Ping
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Lin, Wen-Hui
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Chao, Wun Jie
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Chao, Kuo-Ming
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Lo, Chi-Chun
Most existing approaches focus on examining the values are dangerous for information flow within inter-suspicious modules of cloud applications (apps) in a host by using malware threat analysis, rather than the risk posed by suspicious apps were connected to the cloud computing server. Accordingly, this paper proposes a taint propagation analysis model incorporating a weighted spanning tree analysis scheme to track data with taint marking using several taint checking tools. In the proposed model, Android programs perform dynamic taint propagation to analyse the spread of and risks posed by suspicious apps were connected to the cloud computing server. In determining the risk of taint propagation, risk and defence capability are used for each taint path for assisting a defender in recognising the attack results against network threats caused by malware infection and estimate the losses of associated taint sources. Finally, a case of threat analysis of a typical cyber security attack is presented to demonstrate the proposed approach. Our approach verified the details of an attack sequence for malware infection by incorporating a finite state machine (FSM) to appropriately reflect the real situations at various configuration settings and safeguard deployment. The experimental results proved that the threat analysis model allows a defender to convert the spread of taint propagation to loss and practically estimate the risk of a specific threat by using behavioural analysis with real malware infection.
Using malware for software-defined networking-based smart home security management through a taint checking approach
(2016-08-01)
Wang, Ping
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Chao, Kuo-Ming
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Lo, Chi-Chun
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Lin, Wen-Hui
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Lin, Hsiao-Chung
Numerous security concerns exist in smart home systems in which Internet of Things devices are connected through a home network to enable control using a centralised gateway with a handset device from the Internet. Safeguarding personal information privacy is an increasing concern in smart living services. To guarantee the mobile security of smart living services, security managers use taint checking approaches with dynamic taint propagation analysis operations to examine how a software-defined networking app uses sensitive information and investigate suspicious security vulnerabilities of devices and the effects of the spread of taint propagation over the Internet by identifying taint paths. For solving the dynamic taint propagation analysis problem, most approaches focus on cloud computing applications (apps) with malware threat analysis that involves program vulnerability analyses, rather than on the risk posed by suspicious apps connected to the cloud computing server. Accordingly, this article proposes a taint propagation analysis model incorporating a weighted spanning tree analysis scheme for tracking data with taint marking using several taint checking tools with an open software-defined networking architecture for solving the dynamic taint propagation analysis problem. In the proposed model, Android programs perform dynamic taint propagation to analyse the spread of risks posed by suspicious apps connected to the centralised gateway in a smart home system. In probabilistic risk analysis, risk and defence capability are used for each taint path to assist a defender in recognising the attack results against network threats caused by malware infection and to estimate the losses of associated taint sources. A case of threat analysis of a typical cyber security attack is presented to demonstrate the proposed approach. A new approach was used for verifying the details of an attack sequence for malware infection by incorporating a finite state machine to appropriately represent the real dynamic taint propagation analysis situations at various configuration settings and safeguard deployment. The experimental results proved that the threat analysis model enables a defender to convert the spread of taint propagation to loss and estimate the risk of a specific threat using behavioural analysis associated with 60 families of real malware. Consequently, our scheme was significantly effective in predicting the risk and loss of tainted data propagation for security concerns in smart home systems when the number of taint paths associated with the propagation rules discovered through taint analysis was increased.
Using ontologies to perform threat analysis and develop defensive strategies for mobile security
(2017-03-01)
Wang, Ping
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Chao, Kuo-Ming
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Lo, Chi-Chun
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Wang, Yu-Shih
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資訊管理與財務金融系註：原資管所+財金所
Existing studies on the detection of mobile malware have focused mainly on static analyses performed to examine the code-structure signature of viruses, rather than the dynamic behavioral aspects. By contrast, the unidentified behavior of new mobile viruses using the self-modification, polymorphic, and mutation techniques for variants have largely been ignored. The problem of precision regarding malware variant detection has become one of the key concerns in mobile security. Accordingly, the present study proposed a threat risk analysis model for mobile viruses, using a heuristic approach incorporating both malware behavior analysis and code analysis to generate a virus behavior ontology associated with the Prot,g, platform. The proposed model can not only explicitly identify an attack profile in accordance with structural signature of mobile viruses, but also overcome the uncertainty regarding the probability of an attack being successful. This model is able to achieve this by extending frequent episode rules to investigate the attack profile of a given malware, using specific event sequences associated with the sandbox technique for mobile applications (apps) and hosts. For probabilistic analysis, defense evaluation metrics for each node were used to simulate the results of an attack. The simulations focused specifically on the attack profile of a botnet to assess the threat risk. The validity of the proposed approach was demonstrated numerically by using two malware cyber-attack examples. Overall, the results presented in this paper prove that the proposed scheme offers an effective countermeasure, evaluated using a set of security metrics, for mitigating network threats by considering the interaction between the attack profiles and defense needs.
Using Taint Analysis for Threat Risk of Cloud Applications
(2014-01-01)
Wang, Ping
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Chao, Wun Jie
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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
Most existing approaches to developing cloud applications using threat analysis involve program vulnerability analyses for identifying the security holes associated with malware attacks. New malware attacks can bypass firewall-based detection by bypassing stack protection and by using Hypertext Transfer Protocol logging, kernel hacks, and library hack techniques, and to the cloud applications. In performing threat analysis for unspecified malware attacks, software engineers can use a taint analysis technique for tracking information flows between attack sources (malware) and detect vulnerabilities of targeted network applications. This paper proposes a threat risk analysis model incorporating an improved attack tree analysis scheme for solving the mobile security problem; in the model, Android programs perform taint checking to analyse the risks posed by suspicious applications. In probabilistic risk analysis, defence evaluation metrics are used for each attack path for assisting a defender simulate the attack results against malware attacks and estimate the impact losses. Finally, a case of threat analysis of a typical cyber security attack is presented to demonstrate the proposed approach.