Relevant bibliographies by topics / Fraudulent detection

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Fraudulent detection'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Fraudulent detection.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Fraudulent detection"

1

Awhad, Rahul, Saurabh Jayswal, Adesh More, and Jyoti Kundale. "Fraudulent Face Image Detection." ITM Web of Conferences 32 (2020): 03005. http://dx.doi.org/10.1051/itmconf/20203203005.

Full text
Abstract:
Due to the growing advancements in technology, many software applications are being developed to modify and edit images. Such software can be used to alter images. Nowadays, an altered image is so realistic that it becomes too difficult for a person to identify whether the image is fake or real. Such software applications can be used to alter the image of a person’s face also. So, it becomes very difficult to identify whether the image of the face is real or not. Our proposed system is used to identify whether the image of a face is fake or real. The proposed system makes use of machine learning. The system makes use of a convolution neural network and support vector classifier. Both these machine learning models are trained using real as well as fake images. Both these trained models will take an image as an input and will determine whether the image is fake or real.
APA, Harvard, Vancouver, ISO, and other styles
2

Indriani, Poppy. "FRAUND DIAMOND DALAM MENDETEKSI KECURANGAN LAPORAN KEUANGAN." I-Finance: a Research Journal on Islamic Finance 3, no. 2 (January 29, 2018): 161. http://dx.doi.org/10.19109/ifinance.v3i2.1690.

Full text
Abstract:
Effect of Diamond Fraud in Financial Statement Fraud detection. This study aimed to get empirical evidence regarding the effectiveness of diamond fraud in detecting fraudulent financial statements. Variables - variables of diamond fraud is financial stability is proxied by ACHANGE, external pressure proxied with leverage, financial targets are proxied by the ROA, nature of industry proxied by inventory, ineffective monitoring proxied by BDOUT, audit opinion and change of directors. Financial statement fraud detection in this study using the F-score models. The results of this study indicate that external pressure, financial targets, ineffective monitoring, audit opinion and change of directors does not have influence in detecting fraudulent financial statements. While the financial stability and nature of industry to have an influence in detecting fraudulent financial statements.
APA, Harvard, Vancouver, ISO, and other styles
3

Yu, Frank, and Xiaoyun Yu. "Corporate Lobbying and Fraud Detection." Journal of Financial and Quantitative Analysis 46, no. 6 (June 6, 2011): 1865–91. http://dx.doi.org/10.1017/s0022109011000457.

Full text
Abstract:
AbstractThis paper examines the relation between corporate lobbying and fraud detection. Using data on corporate lobbying expenses between 1998 and 2004, and a sample of large frauds detected during the same period, we find that firms’ lobbying activities make a significant difference in fraud detection: Compared to nonlobbying firms, on average, firms that lobby have a significantly lower hazard rate of being detected for fraud, evade fraud detection 117 days longer, and are 38% less likely to be detected by regulators. In addition, fraudulent firms on average spend 77% more on lobbying than nonfraudulent firms, and they spend 29% more on lobbying during their fraudulent periods than during nonfraudulent periods. The delay in detection leads to a greater distortion in resource allocation during fraudulent periods. It also allows managers to sell more of their shares.
APA, Harvard, Vancouver, ISO, and other styles
4

Jain, Abhisu, Mayank Arora, Anoushka Mehra, and Aviva Munshi. "Anomaly Detection Algorithms in Financial Data." International Journal of Engineering and Advanced Technology 10, no. 5 (June 30, 2021): 76–78. http://dx.doi.org/10.35940/ijeat.e2598.0610521.

Full text
Abstract:
The main aim of this project is to understand and apply the separate approach to classify fraudulent transactions in a database using the Isolation forest algorithm and LOF algorithm instead of the generic Random Forest approach. The model will be able to identify transactions with greater accuracy and we will work towards a more optimal solution by comparing both approaches. The problem of detecting credit card fraud involves modelling past credit card purchases with the perception of those that turned out to be fraud. Then, this model is used to determine whether or not a new transaction is fraudulent. The objective of the project here is to identify 100% of the fraudulent transactions while mitigating the incorrect classifications offraud.
APA, Harvard, Vancouver, ISO, and other styles
5

Indriyani, Ely, and Dhini Suryandari. "DETECTION OF FRAUDULENT FINANCIAL STATEMENT THROUGH PENTAGON THEORY WITH AUDIT COMMITTEE AS MODERATING." EAJ (Economic and Accounting Journal) 4, no. 1 (April 15, 2021): 35. http://dx.doi.org/10.32493/eaj.v4i1.y2021.p35-47.

Full text
Abstract:
This study aims to examine financial targets, financial stability, external pressure, personal financial needs, effective monitoring, nature of industry, total accruals, change of directors, and CEO duality in detecting fraudulent financial statements with the audit committee as the moderating variable. The population of this research is 20 state-owned companies listed on the Indonesia Stock Exchange (BEI) in 2014-2018. Sampling using saturated sampling technique and obtained a final sample of 100 units of analysis. Data collection using documentation techniques. The data analysis technique used regression analysis and Moderated Regression Analysis (MRA). The results of this study indicate that external pressure and the nature of industry have a significant positive effect on the detection of fraudulent financial statements. The audit committee is able to moderate the influence of financial targets, external pressure, nature of industry, and change of directors on the detection of fraudulent financial statements
APA, Harvard, Vancouver, ISO, and other styles
6

Liu, Hankun, Daojing He, and Sammy Chan. "Fraudulent News Headline Detection with Attention Mechanism." Computational Intelligence and Neuroscience 2021 (March 15, 2021): 1–7. http://dx.doi.org/10.1155/2021/6679661.

Full text
Abstract:
E-mail systems and online social media platforms are ideal places for news dissemination, but a serious problem is the spread of fraudulent news headlines. The previous method of detecting fraudulent news headlines was mainly laborious manual review. While the total number of news headlines goes as high as 1.48 million, manual review becomes practically infeasible. For news headline text data, attention mechanism has powerful processing capability. In this paper, we propose the models based on LSTM and attention layer, which fit the context of news headlines efficiently and can detect fraudulent news headlines quickly and accurately. Based on multi-head attention mechanism eschewing recurrent unit and reducing sequential computation, we build Mini-Transformer Deep Learning model to further improve the classification performance.
APA, Harvard, Vancouver, ISO, and other styles
7

Priyadarshini, Aishwarya, Sanhita Mishra, Debani Prasad Mishra, Surender Reddy Salkuti, and Ramakanta Mohanty. "Fraudulent credit card transaction detection using soft computing techniques." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 3 (September 1, 2021): 1634. http://dx.doi.org/10.11591/ijeecs.v23.i3.pp1634-1642.

Full text
Abstract:
<p>Nowadays, fraudulent or deceitful activities associated with financial transactions, predominantly using credit cards have been increasing at an alarming rate and are one of the most prevalent activities in finance industries, corporate companies, and other government organizations. It is therefore essential to incorporate a fraud detection system that mainly consists of intelligent fraud detection techniques to keep in view the consumer and clients’ welfare alike. Numerous fraud detection procedures, techniques, and systems in literature have been implemented by employing a myriad of intelligent techniques including algorithms and frameworks to detect fraudulent and deceitful transactions. This paper initially analyses the data through exploratory data analysis and then proposes various classification models that are implemented using intelligent soft computing techniques to predictively classify fraudulent credit card transactions. Classification algorithms such as K-Nearest neighbor (K-NN), decision tree, random forest (RF), and logistic regression (LR) have been implemented to critically evaluate their performances. The proposed model is computationally efficient, light-weight and can be used for credit card fraudulent transaction detection with better accuracy.</p>
APA, Harvard, Vancouver, ISO, and other styles
8

Bo Sun, Yang Xiao, and Ruhai Wang. "Detection of Fraudulent Usage in Wireless Networks." IEEE Transactions on Vehicular Technology 56, no. 6 (November 2007): 3912–23. http://dx.doi.org/10.1109/tvt.2007.901875.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Pandian, A., and Mohamed Abdul Karim. "Detection of Fraudulent Emails by Authorship Extraction." International Journal of Computer Applications 41, no. 7 (March 31, 2012): 7–12. http://dx.doi.org/10.5120/5551-7619.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Indarto, Stefani Lily, and Imam Ghozali. "Fraud diamond: Detection analysis on the fraudulent financial reporting." Risk Governance and Control: Financial Markets and Institutions 6, no. 4 (2016): 116–23. http://dx.doi.org/10.22495/rcgv6i4c1art1.

Full text
Abstract:
The accounting scandal became one of the reasons for analyzing financial statements in order to minimize fraud against the financial reporting. Therefore, companies use the services of a public accountant to audit the financial statements of companies that are expected to limit the fraudulent practices that increase the public’s confidence in the company’s financial statements. This study aims to detect fraud by using analysis of fraud diamond . This study takes banking companies listed on the Indonesian Stock Exchange in 2009-2014, with a total sample of 149 banks. Based on the results the external pressure, financial stability and capability have influence on fraudulent financial reporting. While target financial, ineffective monitoring and rationalization does not affect the fraudulent financial reporting.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Fraudulent detection"

1

Jóhannsson, Jökull. "Detecting fraudulent users using behaviour analysis." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-224196.

Full text
Abstract:
With the increased global use of online media platforms, there are more opportunities than ever to misuse those platforms or perpetrate fraud. One such fraud is within the music industry, where perpetrators create automated programs, streaming songs to generate revenue or increase popularity of an artist. With growing annual revenue of the digital music industry, there are significant financial incentives for perpetrators with fraud in mind. The focus of the study is extracting user behavioral patterns and utilising them to train and compare multiple supervised classification method to detect fraud.  The machine learning algorithms examined are Logistic Regression, Support Vector Machines, Random Forest and Artificial Neural Networks. The study compares performance of these algorithms trained on imbalanced datasets carrying different fractions of fraud. The trained models are evaluated using the Precision Recall Area Under the Curve (PR AUC) and a F1-score. Results show that the algorithms achieve similar performance when trained on balanced and imbalanced datasets. It also shows that Random Forest outperforms the other methods for all datasets tested in this experiment.
Med den ökande användningen av strömmande media ökar också möjligheterna till missbruk av dessa platformar samt bedrägeri. Ett typiskt fall av bedrägeri är att använda automatiserade program för att strömma media, och därigenom generera intäkter samt att öka en artist popularitet. Med den växande ekonomin kring strömmande media växer också incitamentet till bedrägeriförsök. Denna studies fokus är att finna användarmönster och använda denna kunskap för att träna modeller som kan upptäcka bedrägeriförsök. The maskininlärningsalgoritmer som undersökts är Logistic Regression, Support Vector Machines, Random Forest och Artificiella Neurala Nätverk. Denna studie jämför effektiviteten och precisionen av dessa algoritmer, som tränats på obalanserad data som innehåller olika procentandelar av bedrägeriförsök. Modellerna som genererats av de olika algoritmerna har sedan utvärderas med hjälp av Precision Recall Area Under the Curve (PR AUC) och F1-score. Resultaten av studien visar på liknande prestanda mellan modellerna som genererats av de utvärderade algoritmerna. Detta gäller både när de tränats på balanserad såväl som obalanserad data. Resultaten visar också att Random Forestbaserade modeller genererar bättre resultat för alla dataset som testats i detta experiment.
APA, Harvard, Vancouver, ISO, and other styles
2

Orive, Múgica Iker. "Technical identifiers of fraudulent web pages, a systematic literature review." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19048.

Full text
Abstract:
Fraudulent pages are a danger to which all web users are exposed. These pages have illegitimate purposes such as the theft of sensitive user information. There are a lot of tools available on the market today that are aimed at detecting malicious pages, however, these are not reliable enough and that is why there is still a lot of room for future improvement. Therefore, further analysis of the malicious pages and their characteristics is a key element in protecting users and in the future in eradicating this type of malicious page. A systematic review of the literature has been conducted to generate a list of features that can be used to detect malicious pages and that can ensure a high level of accuracy. During the development of the study, the different articles on the subject have been compared and analysed. For this process of analysis, thematic coding has been used, a qualitative method of analysis, which means that an in-depth understanding of ideas has been pursued. The document presents the already cited list of characteristics as well as offering suggestions and ideas that can be used in the development of future
APA, Harvard, Vancouver, ISO, and other styles
3

Hays, Jerry B. "An Investigation of Management Accountants Intention to Report Fraudulent Accounting Activity: Applying the Theory of Planned Behavior." NSUWorks, 2013. http://nsuworks.nova.edu/hsbe_etd/40.

Full text
Abstract:
The perpetration of accounting fraud still remains a prevalent and significantly costly issue in today's business world. The names Enron, WorldCom, HealthSouth, and Madoff are still all too recent reminders of the devastating cost of financial statement fraud. Management accountants, as preparers of these statements, are in the best position to detect such fraud. Yet there exists no current measurement instrument or methodology designed to measure a management accountant's intention to report fraud. The primary purpose of this study was to investigate the beliefs, concepts, and antecedents that provide the motivation to, or the deterrent from, the reporting of fraudulent accounting activity when witnessed by professional management accountants, and develop an instrument that might measure that motivation. The theoretical basis that framed this research was the Theory of Planned Behavior which provides for an analysis of a participant's attitude, subjective norm, and perceived behavioral control in the development of the intention to perform a specific behavior. The population studied was the U.S. membership of the Institute of Management Accountants, and grant assistance and support was provided by the Institute's Research Foundation. The sample from this population formed a very appropriate representation of experienced, professional management accountants. . No previous research involving this population with the application of the Theory of Planned Behavior and the investigation of the reporting of fraudulent accounting activity had been conducted. Therefore, there were no existing survey instruments that could be applied. The development of an original survey questionnaire to specifically address this research was required. The distribution of this survey questionnaire resulted in 285 complete and usable responses. These responses measured the strength of the participant's positive or negative beliefs concerning the antecedents related to the three exogenous constructs of the Theory of Planned Behavior - attitude, subjective norm, and perceived behavioral control, and the endogenous construct of intention. Structural Equation Modeling (SEM) with measured variables was chosen as the methodology for the analysis of the results measured in the survey responses. Confirmatory Factor Analysis was applied to each construct individually, and construct items were modified to obtain the most reasonable model fit, validity, and reliability. Items were combined into composites to represent the constructs of interest in the theory, as measured by the survey. The relations among the constructs of the Theory of Planned Behavior were then specified using these composites in an SEM model. The results of the data and the findings of the SEM model indicated that professional management accountants form a strong positive intention to report the witnessing of accounting fraud. The positive beliefs that formed the exogenous variables that showed statistically significant effects on the endogenous variable of the formation of a positive intention to report fraudulent accounting activity were: support of the system of internal control, prevention of financial loss, retention of the integrity and ethical values of the profession, perceived support of significant others, and limited impediment due to fear of retaliation. A surprising result was that 32% of all respondents indicated a lack of easy/any access to an anonymous fraud reporting hotline, which is an issue for further research. This study provides additional insight into the concepts, beliefs, and antecedents that form a professional management accountant's intention to report fraudulent accounting activity. The study also presents the basis of a preliminary instrument for the measurement of the intention of management accountants to report fraudulent accounting activity. Further research is suggested for the identification of additional concepts, antecedents, and beliefs related to fraud reporting and for the development of an even more effective measurement instrument.
APA, Harvard, Vancouver, ISO, and other styles
4

Rowson, David. "The problem with fraudulent solicitors : issues of trust, investigation and the self-regulation of the legal profession." Thesis, Teesside University, 2009. http://hdl.handle.net/10149/112684.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Gleichmann, Tobias [Verfasser], Michael [Akademischer Betreuer] Grüning, and Jörg R. [Gutachter] Werner. "The detection of fraudulent financial statements using textual and financial data / Tobias Gleichmann ; Gutachter: Jörg R. Werner ; Betreuer: Michael Grüning." Ilmenau : TU Ilmenau, 2020. http://d-nb.info/1221063383/34.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Andrée, Anton. "Catch the fraudster : The development of a machine learning based fraud filter." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-424464.

Full text
Abstract:
E-commerce has seen a rapid growth the last two decades, making it easy for customers to shop wherever they are. The growth has also led to new kinds of fraudulent activities affecting the customers. To make customers feel safe while shopping online, companies like Resurs Bank are implementing different kinds of fraud filters to freeze transactions that are thought to be fraudulent. The latest type of fraud filter is based on machine learning. While this seems to be a promising technology, data and algorithms need to be tuned properly to the task at hand. This thesis project gives a proof of concept of realizing a machine learning based fraud filter for Resurs Bank. Based on a literature study, available data and explainability requirements, this work opts for a supervised learning approach based on Random Forests with a sliding window to overcome concept drift. The inherent class imbalance of the setting makes the area-under-the-receiver operating-curve a suitable metric. This approach provided promising results that a machine learning based fraud filter can add value to companies like Resurs Bank. An alternative approach on how to incorporate non-numerical features by using recurrent neural networks (RNN) was implemented and compared. The non-numerical feature was transformed by a pre-trained RNN-model to a numerical representation that reflects the features suspiciousness. This new numerical feature was then included in the Random Forest model and the result demonstrated that this approach can add valuable insight to the fraud detection field.
APA, Harvard, Vancouver, ISO, and other styles
7

Ceglia, Cesarina. "A comparison of parametric and non-parametric methods for detecting fraudulent automobile insurance claims." Thesis, California State University, Long Beach, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10147317.

Full text
Abstract:

Fraudulent automobile insurance claims are not only a loss for insurance companies, but also for their policyholders. In order for insurance companies to prevent significant loss from false claims, they must raise their premiums for the policyholders. The goal of this research is to develop a decision making algorithm to determine whether a claim is classified as fraudulent based on the observed characteristics of a claim, which can in turn help prevent future loss. The data includes 923 cases of false claims, 14,497 cases of true claims and 33 describing variables from the years 1994 to 1996. To achieve the goal of this research, parametric and nonparametric methods are used to determine what variables play a major role in detecting fraudulent claims. These methods include logistic regression, the LASSO (least absolute shrinkage and selection operator) method, and Random Forests. This research concluded that a non-parametric Random Forests model classified fraudulent claims with the highest accuracy and best balance between sensitivity and specificity. Variable selection and importance are also implemented to improve the performance at which fraudulent claims are accurately classified.

APA, Harvard, Vancouver, ISO, and other styles
8

Yin, Zi-Hau, and 鄞子豪. "A Hybrid Structure for Fraudulent Financial Statement Detection." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/28936497643396192421.

Full text
Abstract:
碩士
中國文化大學
會計學系
102
The study proposed a novel mechanism for fraudulent financial statement detection. The mechanism consists of two essential parts: one is ensemble feature selection strategy and the other is decision tree. The ensemble feature selection strategy is performed by two techniques, namely t-test and logistic regression. Both of them were used to determine the essential features. After determine the essential features, the selected features were fed into decision tree to construct the forecasting model. The 198 research samples ranged from 2000 to 2010 were considered in this study. According to our research finding, the union ensemble strategy outperforms than other ensemble strategies. In addition, the study also examines the effectiveness of corporate governance indictors. The results indicated that the corporate governance indicators can improve the forecasting performance of the introduced model.
APA, Harvard, Vancouver, ISO, and other styles
9

Chiang, Wen-Yu, and 江玟諭. "Fraudulent Financial Statement Detection Using Data Mining Techniques." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/jqy453.

Full text
Abstract:
碩士
國立臺灣大學
會計學研究所
107
This study attempts to apply data mining techniques on detection of fraudulent financial statements, and investigate whether textual information has information gain for fraudulent financial statements detection. Considering the characteristics of fraud, this study uses Random Forest as data mining techniques to build fraud detection model. Structured variables are selected based on fraud triangle, and textual information is extracted from letter to shareholders and operation review in annual report. The result shows that Random Forest achieved higher classification accuracy than traditional regression model, and the text in annual report has no explicit information gain for distinguishing fraudulent and non-fraudulent companies. However, it is worth noting that the importance of uncertain words in annual report ranks 13 among 83 variables. This implies that tentative words in annual report may be regarded as an important indicator to fraudulent financial statement occurrence.
APA, Harvard, Vancouver, ISO, and other styles
10

Su, Jian-Jia, and 蘇健嘉. "Modeling Real-Time Call Behaviors for Fraudulent Phone Call Detection." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/r4zqka.

Full text
Abstract:
碩士
國立臺灣大學
資訊工程學研究所
107
The main purpose of this thesis is to propose a model that can detect whether a phone number is a fraud in real-time. There are two problems in detecting fraud. Some methods can only apply at the same time interval as training data. On the other hand, a model that can apply to a new phone number have low precision. We propose a modularized call representation and detection model. By two-phases training, our model can generate call representations and uses the call representations to detect fraud. In the first phase, call behavior prediction training allows model generating call representation containing rich information. We then train a simple classifier to detect fraud based on the call representation. Our model outperforms the random baseline and beats baseline model which lacking the call behavior module. As for future work, multi phone number modeling can be used to detect complex fraud because Some fraud is cooperating between several phone numbers.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Fraudulent detection"

1

Ray, Sumantra (Shumone), Sue Fitzpatrick, Rajna Golubic, Susan Fisher, and Sarah Gibbings, eds. Fraud and misconduct. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199608478.003.0025.

Full text
Abstract:
Fraud and misconduct are firstly introduced by clearly defining the meaning of the two words along with what constitutes good data quality and data integrity. Falsification, Fabrication and Plagiarism are discussed. The concept of how regulators view high quality data is described along with the consequences of falsification. The chapter then goes on to present multiple definitions of fraud and misconduct to show similarities and differences between regulatory authorities in the UK and US as compared to other organisations such as the Royal College of Physicians, the Medical Research Council Policy and UK Research Integrity office. Additionally, five landmark and historical cases are presented to demonstrate what constitutes fraud. The General Medical Counsel's role in protecting public safety by ensuring proper medical standards is described along with the UK Research Integrity Office (UKRIO) and the EU Competent Authority roles in conducting investigations of suspected fraud and misconduct cases. The important roles of whistleblowers are described as well as COPE's role in reviewing published medical journal's research. Practical examples are provided to be used for the detection of fraud as well as specific approaches used by the pharmaceutical industry to detect fraudulent data. In the US, databases are available to conduct searches for individuals who have committed fraud such as the Office of Research Integrity (ORI) and the PHS Administration Action Bulletin Board. Additionally, the process for how fraud and misconduct cases are handled in the UK are discussed along with the options available for regulators, such as the MHRA, on sharing information with the public.
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Fraudulent detection"

1

Arunkumar, C., Srijha Kalyan, and Hamsini Ravishankar. "Fraudulent Detection in Healthcare Insurance." In Lecture Notes in Electrical Engineering, 1–9. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9019-1_1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Sánchez-Paniagua, Manuel, Eduardo Fidalgo, Enrique Alegre, and Francisco Jáñez-Martino. "Fraudulent E-Commerce Websites Detection Through Machine Learning." In Lecture Notes in Computer Science, 267–79. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86271-8_23.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Maktabar, Mahdi, Anazida Zainal, Mohd Aizaini Maarof, and Mohamad Nizam Kassim. "Content Based Fraudulent Website Detection Using Supervised Machine Learning Techniques." In Hybrid Intelligent Systems, 294–304. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76351-4_30.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Raghavendra, S. P., Shoieb Ahamed, Ajit Danti, and D. Rohit. "Detection of Fraudulent Alteration of Bank Cheques Using Image Processing Techniques." In Communications in Computer and Information Science, 469–77. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0507-9_39.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Khan, Ashphak, Tejpal Singh, and Amit Sinhal. "Observation Probability in Hidden Markov Model for Credit Card Fraudulent Detection System." In Advances in Intelligent Systems and Computing, 751–60. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1602-5_80.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Khoo, Eric, Anazida Zainal, Nurfadilah Ariffin, Mohd Nizam Kassim, Mohd Aizaini Maarof, and Majid Bakhtiari. "Fraudulent e-Commerce Website Detection Model Using HTML, Text and Image Features." In Advances in Intelligent Systems and Computing, 177–86. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49345-5_19.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Bhushan Sharma, Arpit, and Brijesh Singh. "Performance Evaluation and Identification of Optimal Classifier for Credit Card Fraudulent Detection." In Studies in Computational Intelligence, 137–55. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68291-0_12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Goyal, Nidhi, Niharika Sachdeva, and Ponnurangam Kumaraguru. "Spy the Lie: Fraudulent Jobs Detection in Recruitment Domain using Knowledge Graphs." In Knowledge Science, Engineering and Management, 612–23. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82147-0_50.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Zainab, Kaneez, Namrata Dhanda, and Qamar Abbas. "Analysis of Various Boosting Algorithms Used for Detection of Fraudulent Credit Card Transactions." In Information and Communication Technology for Competitive Strategies (ICTCS 2020), 1083–91. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0882-7_98.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Kusy, Maciej, and Piotr A. Kowalski. "Detection of Fraudulent Credit Card Transactions by Computational Intelligence Models as a Tool in Digital Forensics." In Studies in Computational Intelligence, 205–12. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74970-5_24.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Fraudulent detection"

1

Qayyum, Sameer, Shaheer Mansoor, Adeel Khalid, Khushbakht, Zahid Halim, and A. Rauf Baig. "Fraudulent call detection for mobile networks." In 2010 International Conference on Information and Emerging Technologies (ICIET). IEEE, 2010. http://dx.doi.org/10.1109/iciet.2010.5625718.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Qayyum, Sameer, Shaheer Mansoor, Adeel Khalid, Khushbakht, Zahid Halim, and A. Rauf Baig. "Fraudulent Call Detection for Mobile Networks." In 2010 International Conference on Information Science and Applications. IEEE, 2010. http://dx.doi.org/10.1109/icisa.2010.5480355.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Rajesh, Kartik, Aditya Kumar, and Rajesh Kadu. "Fraudulent News Detection using Machine Learning Approaches." In 2019 Global Conference for Advancement in Technology (GCAT). IEEE, 2019. http://dx.doi.org/10.1109/gcat47503.2019.8978436.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Zheng, Wenbo, Lan Yan, Chao Gou, and Fei-Yue Wang. "Federated Meta-Learning for Fraudulent Credit Card Detection." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/642.

Full text
Abstract:
Credit card transaction fraud costs billions of dollars to card issuers every year. Besides, the credit card transaction dataset is very skewed, there are much fewer samples of frauds than legitimate transactions. Due to the data security and privacy, different banks are usually not allowed to share their transaction datasets. These problems make traditional model difficult to learn the patterns of frauds and also difficult to detect them. In this paper, we introduce a novel framework termed as federated meta-learning for fraud detection. Different from the traditional technologies trained with data centralized in the cloud, our model enables banks to learn fraud detection model with the training data distributed on their own local database. A shared whole model is constructed by aggregating locallycomputed updates of fraud detection model. Banks can collectively reap the benefits of shared model without sharing the dataset and protect the sensitive information of cardholders. To achieve the good performance of classification, we further formulate an improved triplet-like metric learning, and design a novel meta-learning-based classifier, which allows joint comparison with K negative samples in each mini-batch. Experimental results demonstrate that the proposed approach achieves significantly higher performance compared with the other state-of-the-art approaches.
APA, Harvard, Vancouver, ISO, and other styles
5

Mareeswari, V., and S. Sundareswari. "Data stream mining based resilient identity fraudulent detection." In 2014 International Conference on Information Communication and Embedded Systems (ICICES). IEEE, 2014. http://dx.doi.org/10.1109/icices.2014.7033914.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Lee, Vincent, and Haozheng Wei. "Exploratory simulation models for fraudulent detection in Bitcoin system." In 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA). IEEE, 2016. http://dx.doi.org/10.1109/iciea.2016.7603912.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Jian, Li, Yang Ruicheng, and Guo Rongrong. "Self-Organizing Map Method for Fraudulent Financial Data Detection." In 2016 3rd International Conference on Information Science and Control Engineering (ICISCE). IEEE, 2016. http://dx.doi.org/10.1109/icisce.2016.135.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Seemakurthi, Prasad, Shuhao Zhang, and Yibing Qi. "Detection of fraudulent financial reports with machine learning techniques." In 2015 Systems and Information Engineering Design Symposium. IEEE, 2015. http://dx.doi.org/10.1109/sieds.2015.7117005.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

AbdulSattar, Khadija, and Mustafa Hammad. "Fraudulent Transaction Detection in FinTech using Machine Learning Algorithms." In 2020 International Conference on Innovation and Intelligence for Informatics, Computing and Technologies (3ICT). IEEE, 2020. http://dx.doi.org/10.1109/3ict51146.2020.9312025.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

AbdulSattar, Khadija, and Mustafa Hammad. "Fraudulent Transaction Detection in FinTech using Machine Learning Algorithms." In 2020 International Conference on Innovation and Intelligence for Informatics, Computing and Technologies (3ICT). IEEE, 2020. http://dx.doi.org/10.1109/3ict51146.2020.9312025.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Fraudulent detection"

1

Dutra, Lauren M., Matthew C. Farrelly, Brian Bradfield, Jamie Ridenhour, and Jamie Guillory. Modeling the Probability of Fraud in Social Media in a National Cannabis Survey. RTI Press, September 2021. http://dx.doi.org/10.3768/rtipress.2021.mr.0046.2109.

Full text
Abstract:
Cannabis legalization has spread rapidly in the United States. Although national surveys provide robust information on the prevalence of cannabis use, cannabis disorders, and related outcomes, information on knowledge, attitudes, and beliefs (KABs) about cannabis is lacking. To inform the relationship between cannabis legalization and cannabis-related KABs, RTI International launched the National Cannabis Climate Survey (NCCS) in 2016. The survey sampled US residents 18 years or older via mail (n = 2,102), mail-to-web (n = 1,046), and two social media data collections (n = 11,957). This report outlines two techniques that we used to problem-solve several challenges with the resulting data: (1) developing a model for detecting fraudulent cases in social media completes after standard fraud detection measures were insufficient and (2) designing a weighting scheme to pool multiple probability and nonprobability samples. We also describe our approach for validating the pooled dataset. The fraud prevention and detection processes, predictive model of fraud, and the methods used to weight the probability and nonprobability samples can be applied to current and future complex data collections and analysis of existing datasets.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Fraudulent detection' for particular source types:
Journal articles Dissertations / Theses
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography