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
The feature analysis of fraudulent websites is of great significance to the combat,prevention and control of telecom fraud crimes.Aiming to address the shortcomings of existing analytical approaches,i.e.single dimensi...The feature analysis of fraudulent websites is of great significance to the combat,prevention and control of telecom fraud crimes.Aiming to address the shortcomings of existing analytical approaches,i.e.single dimension and venerability to anti-reconnaissance,this paper adopts the Stacking,the ensemble learning algorithm,combines multiple modalities such as text,image and URL,and proposes a multimodal fraudulent website identification method by ensembling heterogeneous models.Crossvalidation is first used in the training of multiple largely different base classifiers that are strong in learning,such as BERT model,residual neural network(ResNet)and logistic regression model.Classification of the text,image and URL features are then performed respectively.The results of the base classifiers are taken as the input of the meta-classifier,and the output of which is eventually used as the final identification.The study indicates that the fusion method is more effective in identifying fraudulent websites than the single-modal method,and the recall is increased by at least 1%.In addition,the deployment of the algorithm to the real Internet environment shows the improvement of the identification accuracy by at least 1.9%compared with other fusion methods.展开更多
Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of ...Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of images.Since the work is done offshore,these agreements or images must be shared through the Internet or stored over the cloud.The breach of privacy,on the other hand,is a potential threat for the image owners as both the Internet and cloud servers are not void of danger.This article proposes a novel algorithm for securing the NDAs in the form of images.As an agreement is signed between the two parties,it will be encrypted before sending to the cloud server or travelling through the public network,the Internet.As the image is input to the algorithm,its pixels would be scrambled through the set of randomly generated rectangles for an arbitrary amount of time.The confusion effects have been realized through an XOR operation between the confused image,and chaotic data.Besides,5D multi-wing hyperchaotic system has been employed to spawn the chaotic vectors due to good properties of chaoticity it has.The machine experimentation and the security analysis through a comprehensive set of validation metric vividly demonstrate the robustness,defiance to the multifarious threats and the prospects for some real-world application of the proposed encryption algorithm for the NDA images.展开更多
Objective: We compared stigma experienced by psychiatric patients and controls in various social domains and hypothesized higher levels of stigma and higher rates of non-disclosure by psychiatric patients. Methods: Ps...Objective: We compared stigma experienced by psychiatric patients and controls in various social domains and hypothesized higher levels of stigma and higher rates of non-disclosure by psychiatric patients. Methods: Psychiatric outpatients and a control group of medical outpatients were assessed for experienced discrimination through a structured questionnaire that included adapted items from the Discrimination and Stigma Scale (DISC-12). Controls were assessed on discrimination related to physical, rather than mental health issues. Statistical analyses were conducted with Pearson’s chi-squared tests and one-way Analyses of Variance (ANOVA). Results: In total, 202 patients comprising 99 psychiatric patients and 103 controls gave consent to the study. Psychiatric patients experienced higher levels of discrimination (F (1, 196) = 24.4, p F (1, 196) = 22.5, p Conclusion: Our study confirmed that psychiatric patients experienced considerable stigma and coped by non-disclosure of their condition.展开更多
This study aims to examine the relationship between audit committee attributes (audit committee independence, financial expertise, meeting frequency, gender diversity, and ethnic composition) and the propensity for ...This study aims to examine the relationship between audit committee attributes (audit committee independence, financial expertise, meeting frequency, gender diversity, and ethnic composition) and the propensity for fraudulent financial reporting. The sample includes 116 fraudulent and non-frandulent firms listed on Bursa Malaysia from 2005 to 2010. The finding of this study indicates that audit committee independence is positively associated with fraudulent financial reporting. The higher the proportion of independent or outside directors on the committee, the higher the possibility of financial fraud, and vice versa. The results also show that the expertise of members of the audit committee is negatively associated with corporate fraud. This suggests that when audit committee members are financially literate, they are more competent to curb fraudulent financial reporting. However, the findings for frequency of audit committee meetings, gender, and ethnicity show that there is no relationship between these variables and corporate fraud. The result of this study is robust after controlling for other firm-specific effects.展开更多
Public institutions are charged with the responsibility of providing essential services for the welfare of the citizens by manipulating the economy's financial flow through public expenditure, taxation, and so on. Th...Public institutions are charged with the responsibility of providing essential services for the welfare of the citizens by manipulating the economy's financial flow through public expenditure, taxation, and so on. The reliance on public institutions to provide public services in Nigeria has resulted in disappointing results, because chief executives of the institutions take less interest in the degree of its success, and this accounts for the high level of fraudulent practices in such institutions. This study, therefore, examined the relationship between forensic auditing and fraudulent practices in Nigerian public institutions. To achieve this purpose, some hypothetical statements were made and a review of relevant literature was explored. The population of the study consisted of the general managers and accountants of 12 public institutions in Nigeria. The data generated were statistically tested with the Pearson Product-Moment Correlation Coefficient. The findings suggest that both the proactive and reactive forensic auditing techniques have a negative significant relationship with fraudulent practices in Nigerian public institutions. Based on the above, it was recommended that: (1) The Economic and Financial Crime Commission (EFCC), the Independent Corrupt Practices Commission (ICPC), and other anti-corruption bodies in Nigeria should have, in their payroll, internal forensic auditors to supplement the duties of the internal auditors; (2) Forensic auditors should regularly undergo training and development programs to acquaint them with relevant knowledge and skills for effective forensic auditing; and (3) Forensic auditing should be made mandatory for public institutions by regulatory authorities rather than being voluntary.展开更多
This paper develops a hypothesis of the four factors from the cause of fraudulent financial reporting in terms of thoughts, culture, motive, opportunity and economic trade-off. Then tests whether independent directors...This paper develops a hypothesis of the four factors from the cause of fraudulent financial reporting in terms of thoughts, culture, motive, opportunity and economic trade-off. Then tests whether independent directors monitor and improve the quality of financial report on the basis of 1 170 firms in China by means of OLS regression. The evidence is consistent with the hypothesis.展开更多
With increasingly rampant telephone fraud activities,the social impact and economic losses caused to China have increased dramatically.Precise,convenient,and efficient fraudulent phone call recognition has become a ch...With increasingly rampant telephone fraud activities,the social impact and economic losses caused to China have increased dramatically.Precise,convenient,and efficient fraudulent phone call recognition has become a challenge since telephone fraud became more varied and covert.To deal with this problem,many researchers have extracted some statistical features of telephone fraud behavior and proposed some machine learning algorithms on the field of fraudulent phone call recognition.In this paper,the calling detail records are utilized to construct a classifier for fraudulent phone call recognition.Meantime,a deep learning approach based on convolutional neural network(CNN)is proposed for better features learning and compared with the existing state-of-the-art machine learning algorithms.It learns phone number and call behavior features of telephone fraud,and improves the accuracy of classification.The evaluation results show that the proposed algorithm outperforms competitive algorithms.展开更多
Qualification of equipment essential to safety in NPPs (nuclear power plants) ensures its capability to perform designated safety functions on demand under postulated service conditions. However, a number of inciden...Qualification of equipment essential to safety in NPPs (nuclear power plants) ensures its capability to perform designated safety functions on demand under postulated service conditions. However, a number of incidents identified by the NRC (Nuclear Regulatory Commission) since 1980s catalysed the US nuclear industry to adopt standard precautions to guard against counterfeit items. The purpose of this paper is to suggest the NFC (near field communication) based equipment qualification management system preventing counterfeit and fraudulent items. The NEQM (NFC based equipment qualification management) system works with the support of legacy systems such as PMS (procurement management system) and FMS (facility management system).展开更多
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supported by Zhejiang Provincial Natural Science Foundation of China(Grant No.LGF20G030001)Ministry of Public Security Science and Technology Plan Project(2022LL16)Key scientific research projects of agricultural and social development in Hangzhou in 2020(202004A06).
文摘The feature analysis of fraudulent websites is of great significance to the combat,prevention and control of telecom fraud crimes.Aiming to address the shortcomings of existing analytical approaches,i.e.single dimension and venerability to anti-reconnaissance,this paper adopts the Stacking,the ensemble learning algorithm,combines multiple modalities such as text,image and URL,and proposes a multimodal fraudulent website identification method by ensembling heterogeneous models.Crossvalidation is first used in the training of multiple largely different base classifiers that are strong in learning,such as BERT model,residual neural network(ResNet)and logistic regression model.Classification of the text,image and URL features are then performed respectively.The results of the base classifiers are taken as the input of the meta-classifier,and the output of which is eventually used as the final identification.The study indicates that the fusion method is more effective in identifying fraudulent websites than the single-modal method,and the recall is increased by at least 1%.In addition,the deployment of the algorithm to the real Internet environment shows the improvement of the identification accuracy by at least 1.9%compared with other fusion methods.
基金This research is fully funded by Universiti Teknologi Malaysia under the UTM Fundamental Research Grant(UTMFR)with Cost Center No Q.K130000.2556.21H14.
文摘Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of images.Since the work is done offshore,these agreements or images must be shared through the Internet or stored over the cloud.The breach of privacy,on the other hand,is a potential threat for the image owners as both the Internet and cloud servers are not void of danger.This article proposes a novel algorithm for securing the NDAs in the form of images.As an agreement is signed between the two parties,it will be encrypted before sending to the cloud server or travelling through the public network,the Internet.As the image is input to the algorithm,its pixels would be scrambled through the set of randomly generated rectangles for an arbitrary amount of time.The confusion effects have been realized through an XOR operation between the confused image,and chaotic data.Besides,5D multi-wing hyperchaotic system has been employed to spawn the chaotic vectors due to good properties of chaoticity it has.The machine experimentation and the security analysis through a comprehensive set of validation metric vividly demonstrate the robustness,defiance to the multifarious threats and the prospects for some real-world application of the proposed encryption algorithm for the NDA images.
文摘Objective: We compared stigma experienced by psychiatric patients and controls in various social domains and hypothesized higher levels of stigma and higher rates of non-disclosure by psychiatric patients. Methods: Psychiatric outpatients and a control group of medical outpatients were assessed for experienced discrimination through a structured questionnaire that included adapted items from the Discrimination and Stigma Scale (DISC-12). Controls were assessed on discrimination related to physical, rather than mental health issues. Statistical analyses were conducted with Pearson’s chi-squared tests and one-way Analyses of Variance (ANOVA). Results: In total, 202 patients comprising 99 psychiatric patients and 103 controls gave consent to the study. Psychiatric patients experienced higher levels of discrimination (F (1, 196) = 24.4, p F (1, 196) = 22.5, p Conclusion: Our study confirmed that psychiatric patients experienced considerable stigma and coped by non-disclosure of their condition.
文摘This study aims to examine the relationship between audit committee attributes (audit committee independence, financial expertise, meeting frequency, gender diversity, and ethnic composition) and the propensity for fraudulent financial reporting. The sample includes 116 fraudulent and non-frandulent firms listed on Bursa Malaysia from 2005 to 2010. The finding of this study indicates that audit committee independence is positively associated with fraudulent financial reporting. The higher the proportion of independent or outside directors on the committee, the higher the possibility of financial fraud, and vice versa. The results also show that the expertise of members of the audit committee is negatively associated with corporate fraud. This suggests that when audit committee members are financially literate, they are more competent to curb fraudulent financial reporting. However, the findings for frequency of audit committee meetings, gender, and ethnicity show that there is no relationship between these variables and corporate fraud. The result of this study is robust after controlling for other firm-specific effects.
文摘Public institutions are charged with the responsibility of providing essential services for the welfare of the citizens by manipulating the economy's financial flow through public expenditure, taxation, and so on. The reliance on public institutions to provide public services in Nigeria has resulted in disappointing results, because chief executives of the institutions take less interest in the degree of its success, and this accounts for the high level of fraudulent practices in such institutions. This study, therefore, examined the relationship between forensic auditing and fraudulent practices in Nigerian public institutions. To achieve this purpose, some hypothetical statements were made and a review of relevant literature was explored. The population of the study consisted of the general managers and accountants of 12 public institutions in Nigeria. The data generated were statistically tested with the Pearson Product-Moment Correlation Coefficient. The findings suggest that both the proactive and reactive forensic auditing techniques have a negative significant relationship with fraudulent practices in Nigerian public institutions. Based on the above, it was recommended that: (1) The Economic and Financial Crime Commission (EFCC), the Independent Corrupt Practices Commission (ICPC), and other anti-corruption bodies in Nigeria should have, in their payroll, internal forensic auditors to supplement the duties of the internal auditors; (2) Forensic auditors should regularly undergo training and development programs to acquaint them with relevant knowledge and skills for effective forensic auditing; and (3) Forensic auditing should be made mandatory for public institutions by regulatory authorities rather than being voluntary.
文摘This paper develops a hypothesis of the four factors from the cause of fraudulent financial reporting in terms of thoughts, culture, motive, opportunity and economic trade-off. Then tests whether independent directors monitor and improve the quality of financial report on the basis of 1 170 firms in China by means of OLS regression. The evidence is consistent with the hypothesis.
基金the National Natural Science Foundation of China(No.61931019).
文摘With increasingly rampant telephone fraud activities,the social impact and economic losses caused to China have increased dramatically.Precise,convenient,and efficient fraudulent phone call recognition has become a challenge since telephone fraud became more varied and covert.To deal with this problem,many researchers have extracted some statistical features of telephone fraud behavior and proposed some machine learning algorithms on the field of fraudulent phone call recognition.In this paper,the calling detail records are utilized to construct a classifier for fraudulent phone call recognition.Meantime,a deep learning approach based on convolutional neural network(CNN)is proposed for better features learning and compared with the existing state-of-the-art machine learning algorithms.It learns phone number and call behavior features of telephone fraud,and improves the accuracy of classification.The evaluation results show that the proposed algorithm outperforms competitive algorithms.
文摘Qualification of equipment essential to safety in NPPs (nuclear power plants) ensures its capability to perform designated safety functions on demand under postulated service conditions. However, a number of incidents identified by the NRC (Nuclear Regulatory Commission) since 1980s catalysed the US nuclear industry to adopt standard precautions to guard against counterfeit items. The purpose of this paper is to suggest the NFC (near field communication) based equipment qualification management system preventing counterfeit and fraudulent items. The NEQM (NFC based equipment qualification management) system works with the support of legacy systems such as PMS (procurement management system) and FMS (facility management system).