Quality is a key factor to ensuring success of e-government websites. Therefore, a definition for high-quality e-government website is required, as well as, an e-government system’s quality evaluation methodology. Th...Quality is a key factor to ensuring success of e-government websites. Therefore, a definition for high-quality e-government website is required, as well as, an e-government system’s quality evaluation methodology. This paper identifies quality attributes that are required to assess the quality of an e-government website, which should be considered by developers during the development of e-government applications. The primary goals are identifying, qualifying, categorizing, and ranking these factors, and then defining the interrelations among these quality factors.展开更多
The fraudulent website image is a vital information carrier for telecom fraud.The efficient and precise recognition of fraudulent website images is critical to combating and dealing with fraudulent websites.Current re...The fraudulent website image is a vital information carrier for telecom fraud.The efficient and precise recognition of fraudulent website images is critical to combating and dealing with fraudulent websites.Current research on image recognition of fraudulent websites is mainly carried out at the level of image feature extraction and similarity study,which have such disadvantages as difficulty in obtaining image data,insufficient image analysis,and single identification types.This study develops a model based on the entropy method for image leader decision and Inception-v3 transfer learning to address these disadvantages.The data processing part of the model uses a breadth search crawler to capture the image data.Then,the information in the images is evaluated with the entropy method,image weights are assigned,and the image leader is selected.In model training and prediction,the transfer learning of the Inception-v3 model is introduced into image recognition of fraudulent websites.Using selected image leaders to train the model,multiple types of fraudulent websites are identified with high accuracy.The experiment proves that this model has a superior accuracy in recognizing images on fraudulent websites compared to other current models.展开更多
Website fingerprinting,also known asWF,is a traffic analysis attack that enables local eavesdroppers to infer a user’s browsing destination,even when using the Tor anonymity network.While advanced attacks based on de...Website fingerprinting,also known asWF,is a traffic analysis attack that enables local eavesdroppers to infer a user’s browsing destination,even when using the Tor anonymity network.While advanced attacks based on deep neural network(DNN)can performfeature engineering and attain accuracy rates of over 98%,research has demonstrated thatDNNis vulnerable to adversarial samples.As a result,many researchers have explored using adversarial samples as a defense mechanism against DNN-based WF attacks and have achieved considerable success.However,these methods suffer from high bandwidth overhead or require access to the target model,which is unrealistic.This paper proposes CMAES-WFD,a black-box WF defense based on adversarial samples.The process of generating adversarial examples is transformed into a constrained optimization problem solved by utilizing the Covariance Matrix Adaptation Evolution Strategy(CMAES)optimization algorithm.Perturbations are injected into the local parts of the original traffic to control bandwidth overhead.According to the experiment results,CMAES-WFD was able to significantly decrease the accuracy of Deep Fingerprinting(DF)and VarCnn to below 8.3%and the bandwidth overhead to a maximum of only 14.6%and 20.5%,respectively.Specially,for Automated Website Fingerprinting(AWF)with simple structure,CMAES-WFD reduced the classification accuracy to only 6.7%and the bandwidth overhead to less than 7.4%.Moreover,it was demonstrated that CMAES-WFD was robust against adversarial training to a certain extent.展开更多
Onemust interact with a specific webpage or website in order to use the Internet for communication,teamwork,and other productive activities.However,because phishing websites look benign and not all website visitors ha...Onemust interact with a specific webpage or website in order to use the Internet for communication,teamwork,and other productive activities.However,because phishing websites look benign and not all website visitors have the same knowledge and skills to inspect the trustworthiness of visited websites,they are tricked into disclosing sensitive information and making them vulnerable to malicious software attacks like ransomware.It is impossible to stop attackers fromcreating phishingwebsites,which is one of the core challenges in combating them.However,this threat can be alleviated by detecting a specific website as phishing and alerting online users to take the necessary precautions before handing over sensitive information.In this study,five machine learning(ML)and DL algorithms—cat-boost(CATB),gradient boost(GB),random forest(RF),multilayer perceptron(MLP),and deep neural network(DNN)—were tested with three different reputable datasets and two useful feature selection techniques,to assess the scalability and consistency of each classifier’s performance on varied dataset sizes.The experimental findings reveal that the CATB classifier achieved the best accuracy across all datasets(DS-1,DS-2,and DS-3)with respective values of 97.9%,95.73%,and 98.83%.The GB classifier achieved the second-best accuracy across all datasets(DS-1,DS-2,and DS-3)with respective values of 97.16%,95.18%,and 98.58%.MLP achieved the best computational time across all datasets(DS-1,DS-2,and DS-3)with respective values of 2,7,and 3 seconds despite scoring the lowest accuracy across all datasets.展开更多
The embracing of ICTs and related technologies has enhanced different approaches for governments worldwide to deliver services to their citizens in a smart way. However, the usage of e-government services by common ci...The embracing of ICTs and related technologies has enhanced different approaches for governments worldwide to deliver services to their citizens in a smart way. However, the usage of e-government services by common citizens is recognized as one of the major setbacks of e-government development in both developed and developing countries. Moreover, government agencies in these countries are facing great challenges in keeping the citizens motivated enough to continue to use e-government services. This research aims to investigate the factors that influence citizens’ trust towards continue use of e-government services in Cameroon. The proposed research model consisted of three main constructs including technological, governmental, risk factors as well as six demographic characteristics (age, gender, educational level, income, internet experience and cultural perception). A five-point Likert scale questionnaire was designed to collect data physically and electronically, 352 valid questionnaires were retrieved. Simple and Multiple regression analysis methods were applied to build an adequate model based on the verification of hypotheses proposed. Based on results obtained, four demographic characteristics (age, education, occupation and income) have influence on citizens’ trust in e-government meanwhile gender and cultural affiliation have no influence. Furthermore, technological factors and governmental factors positively influence trust level in e-government, whereas risk factors have a negative influence on trust level. Deducing from the results, a list of recommendations is proposed to the government of Cameroon in order to reinforce citizens’ trust in e-government services.展开更多
In order to ensure e-government construction healthily,rapidly and orderly develop,an e-government maturity model（EGMM）is proposed based on a software capability maturity model （CMM）and a project management maturi...In order to ensure e-government construction healthily,rapidly and orderly develop,an e-government maturity model（EGMM）is proposed based on a software capability maturity model （CMM）and a project management maturity model（PMMM）. Five levels of maturity in e-government development process are constructed,which include network infrastructure,information serving,information interactive,information sharing and comprehensive integrating.An index system of e-government maturity is put forward,and then an e-government maturity levels evaluation method is presented,which can provide clear,detailed and efficient decision information and investment directions of e-government for decision-makers.The EGMM and its maturity evaluation method are helpful for improving the construction of e-government.展开更多
Taking the knowledge-intensive characteristics of governmental processes into account, an approach to analyzing, extracting and modeling e-government ontology by using both the IDEF5 ontology capture method and the we...Taking the knowledge-intensive characteristics of governmental processes into account, an approach to analyzing, extracting and modeling e-government ontology by using both the IDEF5 ontology capture method and the web ontology language （OWL）, is presented. First, both knowledge-intensive activities and knowledge items can be identified by the analysis of governmental processes. Secondly, the IDEF5 ontology capture method is utilized to extract concepts, terms and statements from these knowledge items, which act as a starting point for ontology refinement and validation. To describe precisely the semantics of the ontologies, the OWL language is employed in our project to formally model these e-government ontologies with the help of Prot6ge-OWL tools. Finally, a case study about applying for social security cards （SSCs） in Shanghai local government is illustrated to demonstrate the effectiveness of the presented approach.展开更多
In order to improve the accuracy and integrality of mining data records from the web, the concepts of isomorphic page and directory page and three algorithms are proposed. An isomorphic web page is a set of web pages ...In order to improve the accuracy and integrality of mining data records from the web, the concepts of isomorphic page and directory page and three algorithms are proposed. An isomorphic web page is a set of web pages that have uniform structure, only differing in main information. A web page which contains many links that link to isomorphic web pages is called a directory page. Algorithm 1 can find directory web pages in a web using adjacent links similar analysis method. It first sorts the link, and then counts the links in each directory. If the count is greater than a given valve then finds the similar sub-page links in the directory and gives the results. A function for an isomorphic web page judgment is also proposed. Algorithm 2 can mine data records from an isomorphic page using a noise information filter. It is based on the fact that the noise information is the same in two isomorphic pages, only the main information is different. Algorithm 3 can mine data records from an entire website using the technology of spider. The experiment shows that the proposed algorithms can mine data records more intactly than the existing algorithms. Mining data records from isomorphic pages is an efficient method.展开更多
Agricultural product trading website is not only an important way to realize the agriculture informatization,but also the main manifestation of the agricultural informatization. Based on the preliminary understanding ...Agricultural product trading website is not only an important way to realize the agriculture informatization,but also the main manifestation of the agricultural informatization. Based on the preliminary understanding of the content and characteristics of China's agricultural product trading website,the paper builds a scientific evaluation indicator system and evaluates 50 typical agricultural product trading websites objectively by using classification and grading method. The results show that the overall construction level of China's agricultural product trading websites is general,and there are obvious differences between regions; the lack of website commercial function and the lag of informatization are the main factors restricting the development of agricultural product trading websites.展开更多
In recent years,the telecommunications sector is no longer limited to traditional communications,but has become the backbone for the use of data,content and digital applications by individuals,governments and companie...In recent years,the telecommunications sector is no longer limited to traditional communications,but has become the backbone for the use of data,content and digital applications by individuals,governments and companies to ensure the continuation of economic and social activity in light of social distancing and total closure inmost countries in the world.Therefore,electronic government(e-Government)andmobile government(m-Government)are the results of technological evolution and innovation.Hence,it is important to investigate the factors that influence the intention to use m-Government services among Jordan’s society.This paper proposed a new m-Government acceptance model in Jordan(AMGS);this model combines the Information System(IS)Success Factor Model and Hofstede Cultural Dimensions Theory.The study was conducted by surveying different groups of the Jordanian community.Astructured questionnaire was used to collect data from203 respondents.Multiple regression analysis has been conducted to analyze the data.The results indicate that the significant predictors of citizen intention to use m-Government services in Jordan are Information Quality,Service Quality,Uncertainty Avoidance,and Indulgence vs.restraint.While,the results also suggest that Power Distance is not a significant predictor of citizen intention to use m-Government services.展开更多
Nowadays, an increasing number of web applications require identification registration. However, the behavior of website registration has not ever been thoroughly studied. We use the database provided by the Chinese S...Nowadays, an increasing number of web applications require identification registration. However, the behavior of website registration has not ever been thoroughly studied. We use the database provided by the Chinese Software Develop Net (CSDN) to provide a complete perspective on this research point. We concentrate on the following three aspects: complexity, correlation, and preference. From these analyses, we draw the following conclusions: firstly, a considerable number of users have not realized the importance of identification and are using very simple identifications that can be attacked very easily. Secondly, there is a strong complexity correlation among the three parts of identification. Thirdly, the top three passwords that users like are 123456789, 12345678 and 11111111, and the top three email providers that they prefer are NETEASE, qq and sina. Further, we provide some suggestions to improve the quality of user passwords.展开更多
A hl-quality website is crucial to a company for a successful e-business. The technique maintainers are always faced with the problem how to locate the prime factors which affect the quality of the websites. In view o...A hl-quality website is crucial to a company for a successful e-business. The technique maintainers are always faced with the problem how to locate the prime factors which affect the quality of the websites. In view of the complexity and fuzziness of BtoC webslte, a quality diagnosis method based on the multl-attribute and multi-layer fuzzy comprehensive evaluation model including all the quality factors is proposed. A simple example of diagnosis on a famous domestic BtoC websites shows the specific steps of this method and proves its validity. The process of quality evaluation and diagnosis system is illustrated and the computer program of diagnosis is Oven.展开更多
Phishing attacks are security attacks that do not affect only individuals’or organizations’websites but may affect Internet of Things(IoT)devices and net-works.IoT environment is an exposed environment for such atta...Phishing attacks are security attacks that do not affect only individuals’or organizations’websites but may affect Internet of Things(IoT)devices and net-works.IoT environment is an exposed environment for such attacks.Attackers may use thingbots software for the dispersal of hidden junk emails that are not noticed by users.Machine and deep learning and other methods were used to design detection methods for these attacks.However,there is still a need to enhance detection accuracy.Optimization of an ensemble classification method for phishing website(PW)detection is proposed in this study.A Genetic Algo-rithm(GA)was used for the proposed method optimization by tuning several ensemble Machine Learning(ML)methods parameters,including Random Forest(RF),AdaBoost(AB),XGBoost(XGB),Bagging(BA),GradientBoost(GB),and LightGBM(LGBM).These were accomplished by ranking the optimized classi-fiers to pick out the best classifiers as a base for the proposed method.A PW data-set that is made up of 4898 PWs and 6157 legitimate websites(LWs)was used for this study's experiments.As a result,detection accuracy was enhanced and reached 97.16 percent.展开更多
文摘Quality is a key factor to ensuring success of e-government websites. Therefore, a definition for high-quality e-government website is required, as well as, an e-government system’s quality evaluation methodology. This paper identifies quality attributes that are required to assess the quality of an e-government website, which should be considered by developers during the development of e-government applications. The primary goals are identifying, qualifying, categorizing, and ranking these factors, and then defining the interrelations among these quality factors.
基金supported by the National Social Science Fund of China(23BGL272)。
文摘The fraudulent website image is a vital information carrier for telecom fraud.The efficient and precise recognition of fraudulent website images is critical to combating and dealing with fraudulent websites.Current research on image recognition of fraudulent websites is mainly carried out at the level of image feature extraction and similarity study,which have such disadvantages as difficulty in obtaining image data,insufficient image analysis,and single identification types.This study develops a model based on the entropy method for image leader decision and Inception-v3 transfer learning to address these disadvantages.The data processing part of the model uses a breadth search crawler to capture the image data.Then,the information in the images is evaluated with the entropy method,image weights are assigned,and the image leader is selected.In model training and prediction,the transfer learning of the Inception-v3 model is introduced into image recognition of fraudulent websites.Using selected image leaders to train the model,multiple types of fraudulent websites are identified with high accuracy.The experiment proves that this model has a superior accuracy in recognizing images on fraudulent websites compared to other current models.
基金the Key JCJQ Program of China:2020-JCJQ-ZD-021-00 and 2020-JCJQ-ZD-024-12.
文摘Website fingerprinting,also known asWF,is a traffic analysis attack that enables local eavesdroppers to infer a user’s browsing destination,even when using the Tor anonymity network.While advanced attacks based on deep neural network(DNN)can performfeature engineering and attain accuracy rates of over 98%,research has demonstrated thatDNNis vulnerable to adversarial samples.As a result,many researchers have explored using adversarial samples as a defense mechanism against DNN-based WF attacks and have achieved considerable success.However,these methods suffer from high bandwidth overhead or require access to the target model,which is unrealistic.This paper proposes CMAES-WFD,a black-box WF defense based on adversarial samples.The process of generating adversarial examples is transformed into a constrained optimization problem solved by utilizing the Covariance Matrix Adaptation Evolution Strategy(CMAES)optimization algorithm.Perturbations are injected into the local parts of the original traffic to control bandwidth overhead.According to the experiment results,CMAES-WFD was able to significantly decrease the accuracy of Deep Fingerprinting(DF)and VarCnn to below 8.3%and the bandwidth overhead to a maximum of only 14.6%and 20.5%,respectively.Specially,for Automated Website Fingerprinting(AWF)with simple structure,CMAES-WFD reduced the classification accuracy to only 6.7%and the bandwidth overhead to less than 7.4%.Moreover,it was demonstrated that CMAES-WFD was robust against adversarial training to a certain extent.
文摘Onemust interact with a specific webpage or website in order to use the Internet for communication,teamwork,and other productive activities.However,because phishing websites look benign and not all website visitors have the same knowledge and skills to inspect the trustworthiness of visited websites,they are tricked into disclosing sensitive information and making them vulnerable to malicious software attacks like ransomware.It is impossible to stop attackers fromcreating phishingwebsites,which is one of the core challenges in combating them.However,this threat can be alleviated by detecting a specific website as phishing and alerting online users to take the necessary precautions before handing over sensitive information.In this study,five machine learning(ML)and DL algorithms—cat-boost(CATB),gradient boost(GB),random forest(RF),multilayer perceptron(MLP),and deep neural network(DNN)—were tested with three different reputable datasets and two useful feature selection techniques,to assess the scalability and consistency of each classifier’s performance on varied dataset sizes.The experimental findings reveal that the CATB classifier achieved the best accuracy across all datasets(DS-1,DS-2,and DS-3)with respective values of 97.9%,95.73%,and 98.83%.The GB classifier achieved the second-best accuracy across all datasets(DS-1,DS-2,and DS-3)with respective values of 97.16%,95.18%,and 98.58%.MLP achieved the best computational time across all datasets(DS-1,DS-2,and DS-3)with respective values of 2,7,and 3 seconds despite scoring the lowest accuracy across all datasets.
文摘The embracing of ICTs and related technologies has enhanced different approaches for governments worldwide to deliver services to their citizens in a smart way. However, the usage of e-government services by common citizens is recognized as one of the major setbacks of e-government development in both developed and developing countries. Moreover, government agencies in these countries are facing great challenges in keeping the citizens motivated enough to continue to use e-government services. This research aims to investigate the factors that influence citizens’ trust towards continue use of e-government services in Cameroon. The proposed research model consisted of three main constructs including technological, governmental, risk factors as well as six demographic characteristics (age, gender, educational level, income, internet experience and cultural perception). A five-point Likert scale questionnaire was designed to collect data physically and electronically, 352 valid questionnaires were retrieved. Simple and Multiple regression analysis methods were applied to build an adequate model based on the verification of hypotheses proposed. Based on results obtained, four demographic characteristics (age, education, occupation and income) have influence on citizens’ trust in e-government meanwhile gender and cultural affiliation have no influence. Furthermore, technological factors and governmental factors positively influence trust level in e-government, whereas risk factors have a negative influence on trust level. Deducing from the results, a list of recommendations is proposed to the government of Cameroon in order to reinforce citizens’ trust in e-government services.
基金The National Key Technology R&D Program of Chinaduring the 11th Five-Year Plan Period(No.2006BAH02A12)the National High Technology Research and Development Program of China(863 Program)(No.2006AA010101)
文摘In order to ensure e-government construction healthily,rapidly and orderly develop,an e-government maturity model（EGMM）is proposed based on a software capability maturity model （CMM）and a project management maturity model（PMMM）. Five levels of maturity in e-government development process are constructed,which include network infrastructure,information serving,information interactive,information sharing and comprehensive integrating.An index system of e-government maturity is put forward,and then an e-government maturity levels evaluation method is presented,which can provide clear,detailed and efficient decision information and investment directions of e-government for decision-makers.The EGMM and its maturity evaluation method are helpful for improving the construction of e-government.
基金The National Natural Science Foundation of China(No.70471023).
文摘Taking the knowledge-intensive characteristics of governmental processes into account, an approach to analyzing, extracting and modeling e-government ontology by using both the IDEF5 ontology capture method and the web ontology language （OWL）, is presented. First, both knowledge-intensive activities and knowledge items can be identified by the analysis of governmental processes. Secondly, the IDEF5 ontology capture method is utilized to extract concepts, terms and statements from these knowledge items, which act as a starting point for ontology refinement and validation. To describe precisely the semantics of the ontologies, the OWL language is employed in our project to formally model these e-government ontologies with the help of Prot6ge-OWL tools. Finally, a case study about applying for social security cards （SSCs） in Shanghai local government is illustrated to demonstrate the effectiveness of the presented approach.
文摘In order to improve the accuracy and integrality of mining data records from the web, the concepts of isomorphic page and directory page and three algorithms are proposed. An isomorphic web page is a set of web pages that have uniform structure, only differing in main information. A web page which contains many links that link to isomorphic web pages is called a directory page. Algorithm 1 can find directory web pages in a web using adjacent links similar analysis method. It first sorts the link, and then counts the links in each directory. If the count is greater than a given valve then finds the similar sub-page links in the directory and gives the results. A function for an isomorphic web page judgment is also proposed. Algorithm 2 can mine data records from an isomorphic page using a noise information filter. It is based on the fact that the noise information is the same in two isomorphic pages, only the main information is different. Algorithm 3 can mine data records from an entire website using the technology of spider. The experiment shows that the proposed algorithms can mine data records more intactly than the existing algorithms. Mining data records from isomorphic pages is an efficient method.
基金Supported by Shandong Provincial Natural Science Foundation(ZR2011DM008)
文摘Agricultural product trading website is not only an important way to realize the agriculture informatization,but also the main manifestation of the agricultural informatization. Based on the preliminary understanding of the content and characteristics of China's agricultural product trading website,the paper builds a scientific evaluation indicator system and evaluates 50 typical agricultural product trading websites objectively by using classification and grading method. The results show that the overall construction level of China's agricultural product trading websites is general,and there are obvious differences between regions; the lack of website commercial function and the lag of informatization are the main factors restricting the development of agricultural product trading websites.
基金This research funded by Al-Zaytoonah University of Jordan.
文摘In recent years,the telecommunications sector is no longer limited to traditional communications,but has become the backbone for the use of data,content and digital applications by individuals,governments and companies to ensure the continuation of economic and social activity in light of social distancing and total closure inmost countries in the world.Therefore,electronic government(e-Government)andmobile government(m-Government)are the results of technological evolution and innovation.Hence,it is important to investigate the factors that influence the intention to use m-Government services among Jordan’s society.This paper proposed a new m-Government acceptance model in Jordan(AMGS);this model combines the Information System(IS)Success Factor Model and Hofstede Cultural Dimensions Theory.The study was conducted by surveying different groups of the Jordanian community.Astructured questionnaire was used to collect data from203 respondents.Multiple regression analysis has been conducted to analyze the data.The results indicate that the significant predictors of citizen intention to use m-Government services in Jordan are Information Quality,Service Quality,Uncertainty Avoidance,and Indulgence vs.restraint.While,the results also suggest that Power Distance is not a significant predictor of citizen intention to use m-Government services.
基金supported by the Foundation for Key Program of Ministry of Education, China under Grant No.311007National Science Foundation Project of China under Grants No. 61202079, No.61170225, No.61271199+1 种基金the Fundamental Research Funds for the Central Universities under Grant No.FRF-TP-09-015Athe Fundamental Research Funds in Beijing Jiaotong University under Grant No.W11JB00630
文摘Nowadays, an increasing number of web applications require identification registration. However, the behavior of website registration has not ever been thoroughly studied. We use the database provided by the Chinese Software Develop Net (CSDN) to provide a complete perspective on this research point. We concentrate on the following three aspects: complexity, correlation, and preference. From these analyses, we draw the following conclusions: firstly, a considerable number of users have not realized the importance of identification and are using very simple identifications that can be attacked very easily. Secondly, there is a strong complexity correlation among the three parts of identification. Thirdly, the top three passwords that users like are 123456789, 12345678 and 11111111, and the top three email providers that they prefer are NETEASE, qq and sina. Further, we provide some suggestions to improve the quality of user passwords.
基金Supported by Key Discipline Project fromScience and Technology Committee of Shanghai(No.04JC14009) and the Research Fund ofDonghua University(No.108 10 0044934)
文摘A hl-quality website is crucial to a company for a successful e-business. The technique maintainers are always faced with the problem how to locate the prime factors which affect the quality of the websites. In view of the complexity and fuzziness of BtoC webslte, a quality diagnosis method based on the multl-attribute and multi-layer fuzzy comprehensive evaluation model including all the quality factors is proposed. A simple example of diagnosis on a famous domestic BtoC websites shows the specific steps of this method and proves its validity. The process of quality evaluation and diagnosis system is illustrated and the computer program of diagnosis is Oven.
基金This research has been funded by the Scientific Research Deanship at University of Ha'il-Saudi Arabia through Project Number RG-20023.
文摘Phishing attacks are security attacks that do not affect only individuals’or organizations’websites but may affect Internet of Things(IoT)devices and net-works.IoT environment is an exposed environment for such attacks.Attackers may use thingbots software for the dispersal of hidden junk emails that are not noticed by users.Machine and deep learning and other methods were used to design detection methods for these attacks.However,there is still a need to enhance detection accuracy.Optimization of an ensemble classification method for phishing website(PW)detection is proposed in this study.A Genetic Algo-rithm(GA)was used for the proposed method optimization by tuning several ensemble Machine Learning(ML)methods parameters,including Random Forest(RF),AdaBoost(AB),XGBoost(XGB),Bagging(BA),GradientBoost(GB),and LightGBM(LGBM).These were accomplished by ranking the optimized classi-fiers to pick out the best classifiers as a base for the proposed method.A PW data-set that is made up of 4898 PWs and 6157 legitimate websites(LWs)was used for this study's experiments.As a result,detection accuracy was enhanced and reached 97.16 percent.
