This document reviews fraud detection in electronic payment gateways. It begins with an abstract that discusses how credit card fraud has increased with the rise of electronic commerce and online payments. It then provides background on payment gateways and discusses common types of credit card fraud like stolen cards, phishing, and internal theft. The literature review covers previous research on using techniques like hidden Markov models, support vector machines, and fingerprint recognition for fraud detection. The proposed system would add an additional layer of security to online transactions by generating a secret code and one-time password for each transaction and only proceeding if the user provides the correct code and password. This is intended to help verify the authenticity of transactions and reduce fraudulent activity.
This document summarizes security issues and challenges with internet banking. It discusses how phishing and malware can be used to steal user credentials and authorize fraudulent transactions. Specifically, it notes that authorization passwords should be related to transaction details to prevent arbitrary transactions, but malware can still change transaction details if the user's device is compromised. It proposes using a dedicated security device to generate authorization passwords based on transaction details, reducing complexity and improving security over smartphones.
Credit Card Duplication and Crime Prevention Using BiometricsIOSR Journals
1. The document proposes using iris recognition and palm vein technology for credit card authentication as a way to improve security over existing methods.
2. Current authentication methods like PINs, signatures, and fingerprints have vulnerabilities like being observable and reproducible.
3. The proposed system uses iris recognition followed by palm vein scanning, comparing the biometric data to stored templates to authenticate the user. If both comparisons match, the transaction would be allowed.
4. Iris patterns and palm vein patterns are unique to each individual and difficult to reproduce, providing improved security over existing authentication methods.
This document summarizes a research paper that proposes using iris recognition and palm vein technology for credit card authentication as a more secure alternative to existing authentication methods. The paper outlines some of the limitations of current authentication methods like PINs, signatures, and fingerprints. It then describes how the proposed system would work, using iris recognition to verify a user's identity followed by palm vein scanning for authentication. The document explains the technical details of how iris recognition and palm vein scanning extract unique biometric patterns and compares them to stored templates to authenticate users. It claims the detection rate of fraud using this dual biometrics approach would be 99.995% compared to traditional methods.
Preventing Internet Fraud By Preventing Identity TheftDiane M. Metcalf
This document summarizes a research study on educating consumers to prevent identity theft and reduce e-commerce fraud. The study involved providing an identity theft prevention class to elementary school staff and measuring its effectiveness through pre- and post-tests. The class covered safe online practices like identifying spoofed emails and calls. It provided an interactive quiz and presentations on topics like privacy on public WiFi and social media. The results showed participants improved their knowledge after the class, correctly answering more questions on the post-test about common fraud scenarios. The study aims to determine if educating consumers empowers them to better protect their personal information and reduce identity theft online.
The document summarizes a data breach at Target Corporation in which customer payment card data was stolen. It discusses how the network was compromised through malware installed on point-of-sale registers, and that credentials from an HVAC vendor were used to access Target's system. The breach could have been prevented through better compliance with security standards and use of EMV chip technology, which is more widely used internationally than in the US.
Replace The Current Antiquated Credit Card SystemWarren Smith
To replace the current antiquated credit card system with origin based credit systems. Offer customers features high on protecting their Assets (identity, money)
This document discusses the changing payments landscape and the need for strong authentication as payment technology advances. It notes that consumers now demand new payment methods through mobile devices and apps, but this increased flexibility has also enabled new forms of payment fraud. Regulators are responding by implementing guidelines requiring two-factor authentication for payments. Phone number verification is presented as an effective method that provides security, privacy and a quality user experience for customers.
This document proposes a new approach for online payment systems that aims to improve security and privacy. It uses a combination of steganography and visual cryptography techniques. In the proposed system, a customer's payment details sent to an online merchant are minimized to only the necessary data for fund transfer verification. The customer's credentials are first encrypted within an image using LSB steganography. This image is then split into two shares using visual cryptography. One share is kept by the customer and the other by a certified authority. During an online purchase, the shares are combined to retrieve the encrypted data and send to the bank for verification, allowing the transaction if the customer is validated. This aims to protect the customer's payment information and prevent misuse
This document summarizes security issues and challenges with internet banking. It discusses how phishing and malware can be used to steal user credentials and authorize fraudulent transactions. Specifically, it notes that authorization passwords should be related to transaction details to prevent arbitrary transactions, but malware can still change transaction details if the user's device is compromised. It proposes using a dedicated security device to generate authorization passwords based on transaction details, reducing complexity and improving security over smartphones.
Credit Card Duplication and Crime Prevention Using BiometricsIOSR Journals
1. The document proposes using iris recognition and palm vein technology for credit card authentication as a way to improve security over existing methods.
2. Current authentication methods like PINs, signatures, and fingerprints have vulnerabilities like being observable and reproducible.
3. The proposed system uses iris recognition followed by palm vein scanning, comparing the biometric data to stored templates to authenticate the user. If both comparisons match, the transaction would be allowed.
4. Iris patterns and palm vein patterns are unique to each individual and difficult to reproduce, providing improved security over existing authentication methods.
This document summarizes a research paper that proposes using iris recognition and palm vein technology for credit card authentication as a more secure alternative to existing authentication methods. The paper outlines some of the limitations of current authentication methods like PINs, signatures, and fingerprints. It then describes how the proposed system would work, using iris recognition to verify a user's identity followed by palm vein scanning for authentication. The document explains the technical details of how iris recognition and palm vein scanning extract unique biometric patterns and compares them to stored templates to authenticate users. It claims the detection rate of fraud using this dual biometrics approach would be 99.995% compared to traditional methods.
Preventing Internet Fraud By Preventing Identity TheftDiane M. Metcalf
This document summarizes a research study on educating consumers to prevent identity theft and reduce e-commerce fraud. The study involved providing an identity theft prevention class to elementary school staff and measuring its effectiveness through pre- and post-tests. The class covered safe online practices like identifying spoofed emails and calls. It provided an interactive quiz and presentations on topics like privacy on public WiFi and social media. The results showed participants improved their knowledge after the class, correctly answering more questions on the post-test about common fraud scenarios. The study aims to determine if educating consumers empowers them to better protect their personal information and reduce identity theft online.
The document summarizes a data breach at Target Corporation in which customer payment card data was stolen. It discusses how the network was compromised through malware installed on point-of-sale registers, and that credentials from an HVAC vendor were used to access Target's system. The breach could have been prevented through better compliance with security standards and use of EMV chip technology, which is more widely used internationally than in the US.
Replace The Current Antiquated Credit Card SystemWarren Smith
To replace the current antiquated credit card system with origin based credit systems. Offer customers features high on protecting their Assets (identity, money)
This document discusses the changing payments landscape and the need for strong authentication as payment technology advances. It notes that consumers now demand new payment methods through mobile devices and apps, but this increased flexibility has also enabled new forms of payment fraud. Regulators are responding by implementing guidelines requiring two-factor authentication for payments. Phone number verification is presented as an effective method that provides security, privacy and a quality user experience for customers.
This document proposes a new approach for online payment systems that aims to improve security and privacy. It uses a combination of steganography and visual cryptography techniques. In the proposed system, a customer's payment details sent to an online merchant are minimized to only the necessary data for fund transfer verification. The customer's credentials are first encrypted within an image using LSB steganography. This image is then split into two shares using visual cryptography. One share is kept by the customer and the other by a certified authority. During an online purchase, the shares are combined to retrieve the encrypted data and send to the bank for verification, allowing the transaction if the customer is validated. This aims to protect the customer's payment information and prevent misuse
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The document discusses the history and development of internet banking. It began in 1981 when four major New York banks offered home banking services using videotext systems. Internet banking allows customers to conduct bank transactions online instead of visiting a physical bank. It involves using electronic means to transfer funds between accounts directly. The document then discusses definitions, types, services, steps for using internet banking, who can use it, how it works, advantages, issues, security risks, problems, and ways to ensure security while banking online.
Online Transaction Fraud Detection using Hidden Markov Model & Behavior AnalysisCSCJournals
Card payment are mostly preferred by many for transactions instead of cash. Due to its convenience, it is the most accepted payment method for offline as well as online purchases, irrespective of region or country the purchase is made. Currently, cards are used for everyday activities, such as online shopping, bill pays, subscriptions, etc. Consequently, there are more chances of fraudulent transactions. Online transactions are the prime target as it does not require real card, only card details are enough and can be stored digitally. The current system detects the fraud transaction after the transaction is completed. Proposed system in this paper, uses Hidden Markov Model (HMM), which is one of the statistical stochastic models used to model randomly changing systems. Using Hidden Markov Model, a fraud transaction can be detected during the time of transaction itself and after 3 attempts of verification card can blocked at the same time. Behavior Analysis (BA) helps to understand the spending habits of cardholder. Hidden Markov Model helps to acquire high-level fraud analysis with a low false alarm ratio.
This document discusses a model for reducing phishing attacks involving SIM card cloning in internet banking. It begins with an introduction describing how internet banking in South Africa has become vulnerable to fraudsters using phishing to steal users' information and then conducting fraudulent SIM swaps to intercept authorization codes. The background section then reviews literature on the causes of this vulnerability, how phishing and SIM cloning is used in these attacks, and the elements needed to reduce such fraudulent transactions, including increased cooperation between banks and mobile operators. The proposed model aims to reflect the actions needed by these groups to address this growing security problem.
This document reviews techniques for online fraud detection. It discusses how increased online activity through social media and ecommerce has led to more fraud. It describes common types of online fraud like identity theft, credit card fraud, and phishing scams. It also outlines statistical and artificial intelligence methods that can be used for fraud detection, like data preprocessing, calculating statistical parameters, clustering, matching algorithms, and forensic analytics. The goal is to detect anomalies in user behavior and transactions that indicate potential fraud.
Survey on Credit Card Fraud Detection Using Different Data Mining Techniquesijsrd.com
In today's world of e-commerce, credit card payment is the most popular and most important mean of payment due to fast technology. As the usage of credit card has increased the number of fraud transaction is also increasing. Credit card fraud is very serious and growing problem throughout the world. This paper represents the survey of various fraud detection techniques through which fraud can be detected. Although there are serious fraud detection technology exits based on data mining, knowledge discovery but they are not capable to detect the fraud at a time when fraudulent transaction are in progress so two techniques Neural Network and Hidden Markov Model(HMM) are capable to detect the fraudulent transaction is in progress. HMM categorizes card holder profile as low, medium, and high spending on their spending behavior. A set of probability is assigned to each cardholder for amount of transaction. The amount of incoming transaction is matched with cardholder previous transaction, if it is justified a predefined threshold value then a transaction is considered as a legitimate else it is considered as a fraud.
The credit card has become the most popular mode of payment for both online as well as
regular purchase, in cases of fraud associated with it are also rising. Credit card frauds are increasing
day by day regardless of the various techniques developed for its detection. Fraudsters are so expert that
they generate new ways for committing fraudulent transactions each day which demands constant
innovation for its detection techniques. Most of the techniques based on Artificial Intelligence, Fuzzy
logic, neural network, logistic regression, naïve Bayesian, Machine learning, Sequence Alignment,
decision tree, Bayesian network, meta learning, Genetic Programming etc., these are evolved in
detecting various credit card fraudulent transactions. This paper presents a survey of various techniques
used in credit card fraud detection mechanisms.
The document discusses security trends in e-banking, including common attacks such as phishing and trojans, security measures implemented by banks like two-factor authentication and secured applications, and emerging technologies like transaction signing using mobile phones or security tokens. It also covers security protocols like SSL and implementations of security standards like EMV's chip authentication program. The outlook presented suggests users and banks will both need different solutions to manage evolving security risks in e-banking.
This document discusses various risks associated with online banking and technology-based banking products and services. It addresses operational risk, credit risk, and reputational risk. Operational risks include internal fraud, external fraud, business disruptions, system failures, and more. Credit risk relates to uncertainty in a counterparty's ability to meet obligations. Reputational risk could result from negative publicity, whether true or not, that leads to loss of customers, revenues, and increased costs. Effective risk management, including risk assessment and mitigation strategies, is important for banks offering online and technology-based services.
This document analyzes the Secure Electronic Transaction (SET) system for securing electronic payments. SET uses cryptography techniques like SSL and nested encryption tunnels to securely transmit payment information between customers, merchants, and payment gateways. The system aims to provide authentication, data confidentiality, non-repudiation, access control, and data integrity. It allows customers to securely purchase items online by encrypting transaction data and verifying identities. The main advantage is it protects payment information and can be easily used, without additional software, by securing the conventional communication channels used for online transactions.
The document discusses the history and types of e-banking and online banking services. It defines e-banking as the automated delivery of traditional banking products and services through electronic channels. It describes different types of online banking websites and services, from informational sites to fully transactional sites that allow funds transfers. The document also discusses debit cards, credit cards, smart cards, and ATM cards as payment methods. It provides an overview of the growth of internet banking in India and reviews literature on evaluations of major bank websites and the history of online banking services.
AN OVERVIEW OF THE BANK FRAUD AND ITS DETECTION TECHNIQUES THROUGH DATA MININGijmnct
Using modern methods of the electronic commerce in daily life transactions is increasing because of the growth and the comfortable access of the people to the internet and social networks. The electronic payment systems are one of the most important electronic commerce methods and the electronic payment fraud is a major problem.For example, the credit card fraud loss increases every year and is regarded as one of the important issues in the credit card institutes and corporations. Therefore, fraud detection is considered as an important research challenge. Fraud reduction is a complicated process requiring a body of knowledge in many scientific fields. Based on the kind of the fraud the banks or the credit card institutes face, different measures may be taken. This paper compares and analyzes the available recent findings on the credit card fraud detection techniques. The objectives of the present study are first to detect different credit card and electronic commerce fraud and then to investigate the strategies used for the purpose of detection.
AN OVERVIEW OF THE BANK FRAUD AND ITS DETECTION TECHNIQUES THROUGH DATA MININGijmnct
Using modern methods of the electronic commerce in daily life transactions is increasing because of the
growth and the comfortable access of the people to the internet and social networks. The electronic
payment systems are one of the most important electronic commerce methods and the electronic payment
fraud is a major problem.For example, the credit card fraud loss increases every year and is regarded as
one of the important issues in the credit card institutes and corporations. Therefore, fraud detection is
considered as an important research challenge. Fraud reduction is a complicated process requiring a body
of knowledge in many scientific fields. Based on the kind of the fraud the banks or the credit card institutes
face, different measures may be taken. This paper compares and analyzes the available recent findings on
the credit card fraud detection techniques. The objectives of the present study are first to detect different
credit card and electronic commerce fraud and then to investigate the strategies used for the purpose of
detection.
This document summarizes an evaluation model for security components in Malaysian internet banking. It presents a literature review on security and threats in internet banking. It then describes a proposed research framework and model to evaluate the security elements, awareness, and usability of internet banking websites in Malaysia. An analysis of six major banking websites found room for improvement in authentication methods, password policies, and increasing user awareness. The evaluation model was tested through a user survey and showed both opportunities and compliance with security requirements.
The document summarizes money laundering methods that utilize the internet. It discusses how the anonymity, speed, and global reach of internet transactions attract money launderers. Specific online services that can be abused include online banking, payment services, gambling, auctions, and digital currencies. Case studies and experiences from Poland are provided. Recommendations to prevent cyber money laundering include monitoring transactions, requiring identity verification for accounts and services, implementing FATF recommendations, and adopting EU directives on electronic money and customer due diligence.
The document discusses the Payment Card Industry Data Security Standard (PCI-DSS) requirements for organizations in India. It provides background on the increasing use of debit/credit cards and e-commerce transactions, and the need to protect cardholder data. It describes the intended audience of the PCI-DSS standard, provides details on compliance requirements, certification processes, and challenges organizations face adhering to PCI-DSS. It also discusses instances of credit card fraud in India and how adherence to PCI-DSS can help mitigate such risks.
Automated teller machine (ATM) theft is a major problem, with estimates of 5,500 crimes per year in the US. Criminals use various methods like card skimming, card trapping, and deposit fraud to steal people's card information and PINs to withdraw money from their accounts. Banks can help prevent such theft by implementing better security technologies like biometrics and alert systems, as well as educating customers about common scams.
This document discusses security risks in EMV chip credit card transactions and proposed solutions. It begins by explaining the need to transition from magnetic stripe cards to EMV chip cards due to high fraud rates with magnetic stripe cards. Some key reasons discussed are that magnetic stripe card data is unencrypted and vulnerable to skimming and cloning attacks. EMV chip cards address these issues through technologies like static data authentication, dynamic data authentication, and cryptograms that are unique to each transaction. However, the document also notes that EMV chip technology still has some vulnerabilities and the final sections propose solutions to issues like relay attacks in EMV and security problems with near field communication based payments.
This document provides an overview of e-banking in India, including definitions, forms of e-banking such as internet banking, ATMs, telebanking, smart cards, debit cards, and e-cheques. It discusses the global e-banking landscape and trends, focusing on experiences in Asia, the US, and Europe. For India specifically, it notes that e-banking is still nascent but growing in importance. Key challenges include security concerns and technological development, which Indian banks and regulators are working to address through guidelines and initiatives.
This document provides an overview of various banking services including mobile banking, debit cards, safety lockers, travellers cheques, telegraphic transfers, ATMs, credit cards, seven day banking, gift cheques, and electronic funds transfer. It describes each service and its key features. Mobile banking allows customers to conduct financial transactions remotely using a mobile device. Debit cards can be used instead of cash for purchases and are deducted directly from the user's bank balance. Safety lockers provide secure storage of valuables. Travellers cheques minimize risk when traveling. Telegraphic transfers electronically transfer funds between accounts. ATMs provide automated access to accounts. Credit cards allow purchases to be paid later. Seven day banking offers banking
Credit Card Fraud Detection System Using Machine Learning AlgorithmIRJET Journal
This document discusses using machine learning algorithms to detect credit card fraud. It begins with an abstract that introduces credit card fraud as an increasing problem and machine learning as a solution. The introduction provides more background on credit card fraud and detection methods. It then discusses several machine learning algorithms that can be used for credit card fraud detection, including logistic regression, decision trees, random forests, and XGBoost. It concludes that hybrid models combining individual algorithms performed best on a publicly available credit card dataset, with the highest Matthews correlation coefficient of 0.823. References are provided on related work in credit card fraud detection techniques.
Credit Cards Frauds and Cybersecurity Threats Machine Learning Detection Algo...ijtsrd
Credit and Debit cards have become the choice mode of payment online as a result of the proliferation of electronic transactions and advancement in Information and Communication Technology ICT . Because of the increased use of credit cards for payment online, the number of fraud cases associated with it has also increased scammers and fraudsters are stealing credit card information of victims online and thereby stealing their monies. There is the need therefore to stop or abate these frauds using very powerful fraud detection system that detects patterns of credit card frauds in order to prevent it from occurring. In this paper we x rayed the concept of credit card frauds and how they are carried out by fraudsters. Python 3.7.6 programming language, Jupyter Notebook 6.0.3 and Anaconda Navigator 1.9.12 were used as experimental test bed. Also, we implemented two different supervised machine learning algorithms on an imbalanced dataset such as Decision Tree and Random forest techniques. A comparative analysis of the credit card detection capabilities of these machine learning algorithms were carried out to ascertain the best detection algorithm using different performance evaluation metrics such as accuracy, precision, recall, f1 score, confusion matrix. Experimental results showed that Random Forest outperformed Decision Tree algorithm slightly in performance metrics used for performance evaluation. Obodoeze Fidelis C. | Oliver Ifeoma Catherine | Onyemachi George Olisamaka | Udeh Ifeanyi Frank Gideon | Obiokafor, Ifeyinwa Nkemdilim "Credit Cards Frauds and Cybersecurity Threats: Machine Learning Detection Algorithms as Countermeasures" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-7 , December 2022, URL: https://www.ijtsrd.com/papers/ijtsrd52440.pdf Paper URL: https://www.ijtsrd.com/computer-science/computer-security/52440/credit-cards-frauds-and-cybersecurity-threats-machine-learning-detection-algorithms-as-countermeasures/obodoeze-fidelis-c
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The document discusses the history and development of internet banking. It began in 1981 when four major New York banks offered home banking services using videotext systems. Internet banking allows customers to conduct bank transactions online instead of visiting a physical bank. It involves using electronic means to transfer funds between accounts directly. The document then discusses definitions, types, services, steps for using internet banking, who can use it, how it works, advantages, issues, security risks, problems, and ways to ensure security while banking online.
Online Transaction Fraud Detection using Hidden Markov Model & Behavior AnalysisCSCJournals
Card payment are mostly preferred by many for transactions instead of cash. Due to its convenience, it is the most accepted payment method for offline as well as online purchases, irrespective of region or country the purchase is made. Currently, cards are used for everyday activities, such as online shopping, bill pays, subscriptions, etc. Consequently, there are more chances of fraudulent transactions. Online transactions are the prime target as it does not require real card, only card details are enough and can be stored digitally. The current system detects the fraud transaction after the transaction is completed. Proposed system in this paper, uses Hidden Markov Model (HMM), which is one of the statistical stochastic models used to model randomly changing systems. Using Hidden Markov Model, a fraud transaction can be detected during the time of transaction itself and after 3 attempts of verification card can blocked at the same time. Behavior Analysis (BA) helps to understand the spending habits of cardholder. Hidden Markov Model helps to acquire high-level fraud analysis with a low false alarm ratio.
This document discusses a model for reducing phishing attacks involving SIM card cloning in internet banking. It begins with an introduction describing how internet banking in South Africa has become vulnerable to fraudsters using phishing to steal users' information and then conducting fraudulent SIM swaps to intercept authorization codes. The background section then reviews literature on the causes of this vulnerability, how phishing and SIM cloning is used in these attacks, and the elements needed to reduce such fraudulent transactions, including increased cooperation between banks and mobile operators. The proposed model aims to reflect the actions needed by these groups to address this growing security problem.
This document reviews techniques for online fraud detection. It discusses how increased online activity through social media and ecommerce has led to more fraud. It describes common types of online fraud like identity theft, credit card fraud, and phishing scams. It also outlines statistical and artificial intelligence methods that can be used for fraud detection, like data preprocessing, calculating statistical parameters, clustering, matching algorithms, and forensic analytics. The goal is to detect anomalies in user behavior and transactions that indicate potential fraud.
Survey on Credit Card Fraud Detection Using Different Data Mining Techniquesijsrd.com
In today's world of e-commerce, credit card payment is the most popular and most important mean of payment due to fast technology. As the usage of credit card has increased the number of fraud transaction is also increasing. Credit card fraud is very serious and growing problem throughout the world. This paper represents the survey of various fraud detection techniques through which fraud can be detected. Although there are serious fraud detection technology exits based on data mining, knowledge discovery but they are not capable to detect the fraud at a time when fraudulent transaction are in progress so two techniques Neural Network and Hidden Markov Model(HMM) are capable to detect the fraudulent transaction is in progress. HMM categorizes card holder profile as low, medium, and high spending on their spending behavior. A set of probability is assigned to each cardholder for amount of transaction. The amount of incoming transaction is matched with cardholder previous transaction, if it is justified a predefined threshold value then a transaction is considered as a legitimate else it is considered as a fraud.
The credit card has become the most popular mode of payment for both online as well as
regular purchase, in cases of fraud associated with it are also rising. Credit card frauds are increasing
day by day regardless of the various techniques developed for its detection. Fraudsters are so expert that
they generate new ways for committing fraudulent transactions each day which demands constant
innovation for its detection techniques. Most of the techniques based on Artificial Intelligence, Fuzzy
logic, neural network, logistic regression, naïve Bayesian, Machine learning, Sequence Alignment,
decision tree, Bayesian network, meta learning, Genetic Programming etc., these are evolved in
detecting various credit card fraudulent transactions. This paper presents a survey of various techniques
used in credit card fraud detection mechanisms.
The document discusses security trends in e-banking, including common attacks such as phishing and trojans, security measures implemented by banks like two-factor authentication and secured applications, and emerging technologies like transaction signing using mobile phones or security tokens. It also covers security protocols like SSL and implementations of security standards like EMV's chip authentication program. The outlook presented suggests users and banks will both need different solutions to manage evolving security risks in e-banking.
This document discusses various risks associated with online banking and technology-based banking products and services. It addresses operational risk, credit risk, and reputational risk. Operational risks include internal fraud, external fraud, business disruptions, system failures, and more. Credit risk relates to uncertainty in a counterparty's ability to meet obligations. Reputational risk could result from negative publicity, whether true or not, that leads to loss of customers, revenues, and increased costs. Effective risk management, including risk assessment and mitigation strategies, is important for banks offering online and technology-based services.
This document analyzes the Secure Electronic Transaction (SET) system for securing electronic payments. SET uses cryptography techniques like SSL and nested encryption tunnels to securely transmit payment information between customers, merchants, and payment gateways. The system aims to provide authentication, data confidentiality, non-repudiation, access control, and data integrity. It allows customers to securely purchase items online by encrypting transaction data and verifying identities. The main advantage is it protects payment information and can be easily used, without additional software, by securing the conventional communication channels used for online transactions.
The document discusses the history and types of e-banking and online banking services. It defines e-banking as the automated delivery of traditional banking products and services through electronic channels. It describes different types of online banking websites and services, from informational sites to fully transactional sites that allow funds transfers. The document also discusses debit cards, credit cards, smart cards, and ATM cards as payment methods. It provides an overview of the growth of internet banking in India and reviews literature on evaluations of major bank websites and the history of online banking services.
AN OVERVIEW OF THE BANK FRAUD AND ITS DETECTION TECHNIQUES THROUGH DATA MININGijmnct
Using modern methods of the electronic commerce in daily life transactions is increasing because of the growth and the comfortable access of the people to the internet and social networks. The electronic payment systems are one of the most important electronic commerce methods and the electronic payment fraud is a major problem.For example, the credit card fraud loss increases every year and is regarded as one of the important issues in the credit card institutes and corporations. Therefore, fraud detection is considered as an important research challenge. Fraud reduction is a complicated process requiring a body of knowledge in many scientific fields. Based on the kind of the fraud the banks or the credit card institutes face, different measures may be taken. This paper compares and analyzes the available recent findings on the credit card fraud detection techniques. The objectives of the present study are first to detect different credit card and electronic commerce fraud and then to investigate the strategies used for the purpose of detection.
AN OVERVIEW OF THE BANK FRAUD AND ITS DETECTION TECHNIQUES THROUGH DATA MININGijmnct
Using modern methods of the electronic commerce in daily life transactions is increasing because of the
growth and the comfortable access of the people to the internet and social networks. The electronic
payment systems are one of the most important electronic commerce methods and the electronic payment
fraud is a major problem.For example, the credit card fraud loss increases every year and is regarded as
one of the important issues in the credit card institutes and corporations. Therefore, fraud detection is
considered as an important research challenge. Fraud reduction is a complicated process requiring a body
of knowledge in many scientific fields. Based on the kind of the fraud the banks or the credit card institutes
face, different measures may be taken. This paper compares and analyzes the available recent findings on
the credit card fraud detection techniques. The objectives of the present study are first to detect different
credit card and electronic commerce fraud and then to investigate the strategies used for the purpose of
detection.
This document summarizes an evaluation model for security components in Malaysian internet banking. It presents a literature review on security and threats in internet banking. It then describes a proposed research framework and model to evaluate the security elements, awareness, and usability of internet banking websites in Malaysia. An analysis of six major banking websites found room for improvement in authentication methods, password policies, and increasing user awareness. The evaluation model was tested through a user survey and showed both opportunities and compliance with security requirements.
The document summarizes money laundering methods that utilize the internet. It discusses how the anonymity, speed, and global reach of internet transactions attract money launderers. Specific online services that can be abused include online banking, payment services, gambling, auctions, and digital currencies. Case studies and experiences from Poland are provided. Recommendations to prevent cyber money laundering include monitoring transactions, requiring identity verification for accounts and services, implementing FATF recommendations, and adopting EU directives on electronic money and customer due diligence.
The document discusses the Payment Card Industry Data Security Standard (PCI-DSS) requirements for organizations in India. It provides background on the increasing use of debit/credit cards and e-commerce transactions, and the need to protect cardholder data. It describes the intended audience of the PCI-DSS standard, provides details on compliance requirements, certification processes, and challenges organizations face adhering to PCI-DSS. It also discusses instances of credit card fraud in India and how adherence to PCI-DSS can help mitigate such risks.
Automated teller machine (ATM) theft is a major problem, with estimates of 5,500 crimes per year in the US. Criminals use various methods like card skimming, card trapping, and deposit fraud to steal people's card information and PINs to withdraw money from their accounts. Banks can help prevent such theft by implementing better security technologies like biometrics and alert systems, as well as educating customers about common scams.
This document discusses security risks in EMV chip credit card transactions and proposed solutions. It begins by explaining the need to transition from magnetic stripe cards to EMV chip cards due to high fraud rates with magnetic stripe cards. Some key reasons discussed are that magnetic stripe card data is unencrypted and vulnerable to skimming and cloning attacks. EMV chip cards address these issues through technologies like static data authentication, dynamic data authentication, and cryptograms that are unique to each transaction. However, the document also notes that EMV chip technology still has some vulnerabilities and the final sections propose solutions to issues like relay attacks in EMV and security problems with near field communication based payments.
This document provides an overview of e-banking in India, including definitions, forms of e-banking such as internet banking, ATMs, telebanking, smart cards, debit cards, and e-cheques. It discusses the global e-banking landscape and trends, focusing on experiences in Asia, the US, and Europe. For India specifically, it notes that e-banking is still nascent but growing in importance. Key challenges include security concerns and technological development, which Indian banks and regulators are working to address through guidelines and initiatives.
This document provides an overview of various banking services including mobile banking, debit cards, safety lockers, travellers cheques, telegraphic transfers, ATMs, credit cards, seven day banking, gift cheques, and electronic funds transfer. It describes each service and its key features. Mobile banking allows customers to conduct financial transactions remotely using a mobile device. Debit cards can be used instead of cash for purchases and are deducted directly from the user's bank balance. Safety lockers provide secure storage of valuables. Travellers cheques minimize risk when traveling. Telegraphic transfers electronically transfer funds between accounts. ATMs provide automated access to accounts. Credit cards allow purchases to be paid later. Seven day banking offers banking
Credit Card Fraud Detection System Using Machine Learning AlgorithmIRJET Journal
This document discusses using machine learning algorithms to detect credit card fraud. It begins with an abstract that introduces credit card fraud as an increasing problem and machine learning as a solution. The introduction provides more background on credit card fraud and detection methods. It then discusses several machine learning algorithms that can be used for credit card fraud detection, including logistic regression, decision trees, random forests, and XGBoost. It concludes that hybrid models combining individual algorithms performed best on a publicly available credit card dataset, with the highest Matthews correlation coefficient of 0.823. References are provided on related work in credit card fraud detection techniques.
Credit Cards Frauds and Cybersecurity Threats Machine Learning Detection Algo...ijtsrd
Credit and Debit cards have become the choice mode of payment online as a result of the proliferation of electronic transactions and advancement in Information and Communication Technology ICT . Because of the increased use of credit cards for payment online, the number of fraud cases associated with it has also increased scammers and fraudsters are stealing credit card information of victims online and thereby stealing their monies. There is the need therefore to stop or abate these frauds using very powerful fraud detection system that detects patterns of credit card frauds in order to prevent it from occurring. In this paper we x rayed the concept of credit card frauds and how they are carried out by fraudsters. Python 3.7.6 programming language, Jupyter Notebook 6.0.3 and Anaconda Navigator 1.9.12 were used as experimental test bed. Also, we implemented two different supervised machine learning algorithms on an imbalanced dataset such as Decision Tree and Random forest techniques. A comparative analysis of the credit card detection capabilities of these machine learning algorithms were carried out to ascertain the best detection algorithm using different performance evaluation metrics such as accuracy, precision, recall, f1 score, confusion matrix. Experimental results showed that Random Forest outperformed Decision Tree algorithm slightly in performance metrics used for performance evaluation. Obodoeze Fidelis C. | Oliver Ifeoma Catherine | Onyemachi George Olisamaka | Udeh Ifeanyi Frank Gideon | Obiokafor, Ifeyinwa Nkemdilim "Credit Cards Frauds and Cybersecurity Threats: Machine Learning Detection Algorithms as Countermeasures" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-7 , December 2022, URL: https://www.ijtsrd.com/papers/ijtsrd52440.pdf Paper URL: https://www.ijtsrd.com/computer-science/computer-security/52440/credit-cards-frauds-and-cybersecurity-threats-machine-learning-detection-algorithms-as-countermeasures/obodoeze-fidelis-c
A Comparative Study on Online Transaction Fraud Detection by using Machine Le...IRJET Journal
This document summarizes a study that used machine learning and Python to detect online transaction fraud. It describes how online transactions and fraud are increasing. The study used a real credit card dataset to train models like KNN, NB, and SVM to detect fraudulent transactions based on user behavior patterns and restrict fraudulent users after three failed attempts. The goal was to develop a system that can detect fraud in real-time and prevent losses for banks and credit card users.
The document discusses fraud risks in e-banking and provides recommendations to address them. It summarizes the evolution of e-banking in India, benefits and vulnerabilities. Examples of major data breaches globally and in India are provided. Common e-banking fraud types like phishing, malware attacks etc. are described along with their characteristics. The document recommends controls that can be implemented by banks and users to enhance security of e-banking transactions and detect frauds.
The main incentive for the use of electronic commerce (E-commerce) and spread on a large scale is that
most of business activities need payment system. As E-commerce requires an efficient payment system
which is stable and secure for supporting electronically commerce. This paper proposed to enforce SET,
SSL protocols for encrypting e-payment information. It also presented several methods to take under
consideration to avoid fraud and keep our site safe.
The main incentive for the use of electronic commerce (E-commerce) and spread on a large scale is that most of business activities need payment system. As E-commerce requires an efficient payment system which is stable and secure for supporting electronically commerce. This paper proposed to enforce SET, SSL protocols for encrypting e-payment information. It also presented several methods to take under consideration to avoid fraud and keep our site safe.
The main incentive for the use of electronic commerce (E-commerce) and spread on a large scale is that most of business activities need payment system. As E-commerce requires an efficient payment system which is stable and secure for supporting electronically commerce. This paper proposed to enforce SET, SSL protocols for encrypting e-payment information. It also presented several methods to take under consideration to avoid fraud and keep our site safe.
IRJET- Credit Card Fraud Detection using Hybrid ModelsIRJET Journal
This document discusses credit card fraud detection using hybrid models. It begins by introducing the problem of credit card fraud and how billions of dollars are lost to fraud each year. The document then discusses how standard models and hybrid techniques using AdaBoost and majority voting are used to detect fraud. Experimental results on a public credit card dataset and a private dataset from a financial institution show that the majority voting technique achieves good accuracy in detecting fraud cases. The key challenges in credit card fraud detection are also summarized, such as imbalanced data, different costs of misclassification, overlapping data patterns, lack of flexibility, and fraud detection costs.
This document provides an overview of internet payment systems and electronic payment methods. It discusses key topics like:
- Common internet payment methods including credit cards, digital cash, electronic checks, and payment gateways.
- Electronic payment security issues and protocols like Secure Electronic Transaction (SET) that aim to securely transmit payment information online.
- Specific payment technologies like e-cash, e-wallets, smart cards, and their processing workflows.
- Regulations and growth of electronic payments in India, highlighting channels used and key players in the payments processing market.
The document aims to educate about the various methods available for collecting payments online from customers, while maintaining security of financial information transmitted over the internet.
Secure Payments: How Card Issuers and Merchants Can Stay Ahead of FraudstersCognizant
Our latest research reveals that merchants and card issuers should take a layered approach to mitigating risk, by working with consumers to improve fraud detection and prevention.
Payment card fraud costs billions each year and is becoming more sophisticated. An online carding course was designed to teach novice criminals carding techniques over 6 weeks with 20 lectures and instructors. The course cost nearly $1000 and taught students how to make thousands each month. It covered buying stolen credit card details from online shops, committing fraud, and cashing out illegally obtained goods. Understanding these courses helps defenders address the latest criminal methods.
Transactions Using Bio-Metric AuthenticationIRJET Journal
This document proposes a new method for securing ATM and point-of-sale transactions using biometric authentication. The current systems that rely only on PINs are not fully secure as PINs can be stolen. The proposed method uses facial recognition combined with PIN entry to verify the identity of the user. It describes capturing a photo of the user's face at the ATM/point-of-sale machine and matching it with their biometric database profile for authentication. If an unauthorized person tries to use the card, their photo would be sent to the registered user for verification before allowing the transaction. This provides improved security over existing authentication methods.
1) The document discusses using hidden Markov models to analyze credit card transaction patterns to detect fraudulent activity. It analyzes the spending profiles of cardholders over their last 20 transactions to identify anomalies.
2) The proposed model uses low, medium, and high price ranges to classify transaction amounts and detect deviations from normal spending patterns.
3) The analysis calculates the percentage of transactions in each spending profile category based on past transactions to identify unusual activity. Detecting fraudulent transactions in real-time can prevent further losses.
Analysis of Spending Pattern on Credit Card Fraud DetectionIOSR Journals
1) The document proposes using hidden Markov models to analyze credit card transaction patterns and detect fraudulent transactions. It examines spending profiles of cardholders to identify anomalies compared to normal usage.
2) The key aspects of the proposed system include modeling the different types of purchases as hidden states and transaction amounts as observations in an HMM. The HMM can then detect fraudulent transactions based on deviations from a cardholder's typical spending pattern.
3) Preliminary results show the approach can effectively identify a cardholder's spending profile based on historical transactions and flag transactions inconsistent with that profile as potentially fraudulent.
The series of presentations contains the information about "Management Information System" subject of SEIT for University of Pune.
Subject Teacher: Tushar B Kute (Sandip Institute of Technology and Research Centre, Nashik)
http://www.tusharkute.com
IRJET- Using Fingerprint, Pycrypto, and Mobile Banking App, to Withdraw Cash ...IRJET Journal
This document proposes a new system for withdrawing cash from ATMs using fingerprint authentication on a mobile banking app. The system aims to improve security and reduce transaction times. It proposes using fingerprint biometrics, the mobile app, and Pycrypto software to encrypt communications and generate a one-time password tied to the user's fingerprint. If implemented, the system could allow cash withdrawals in 5 seconds compared to 30 seconds for traditional ATM systems, while improving security against eavesdropping and other attacks. The system aims to save customers time and improve privacy during ATM transactions in developing countries.
1) Ethiopia has high potential for e-commerce growth given its large population and rapid infrastructure development, but card-not-present transactions present security risks.
2) 3D Secure is a global standard that adds an extra authentication layer for online payments, reducing fraud liability for merchants. It works by requesting additional identity verification from the cardholder during checkout.
3) While 3D Secure reduces fraud, some countries still experience high costs of billions from card-not-present fraud each year, showing the ongoing need to implement secure online payment solutions.
Next generation payment technologies gain acceptanceDawn Kehr
Next generation payment technologies like contactless smart cards, biometrics, and e-commerce payment tools are gaining acceptance due to offering convenience and new security features. These technologies include contactless credit and debit cards that use radio frequencies for payment, fingerprint scanners for retail purchases, and online services like PayPal that allow shopping without sharing credit card information. While improving security, data protection is still a shared responsibility of technology providers and businesses implementing these solutions.
This document discusses enhancing security features for automated teller machines (ATMs) from a Ghanaian perspective. It proposes using biometric authentication, like fingerprint scanning, instead of personal identification numbers (PINs) for ATM access. The document provides an overview of common ATM fraud and recommends approaches to prevent fraud, including developing a prototype biometrically equipped ATM model. It notes that ATMs in Ghanaian banks currently do not use biometric technology, so the research aims to increase security.
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What is artificial intelligence? Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the intellectual processes characteristic of humans, such as the ability to reason.
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