Fraud Detection Fundamentals
Expert-defined terms from the Fraud Detection and Prevention course at LearnUNI. Free to read, free to share, paired with a professional course.
Abnormality Detection refers to the process of identifying patterns or be… #
Related terms include Anomaly detection and Outlier analysis. Abnormality detection is crucial in fraud detection as it helps to identify potential threats that may have gone unnoticed by traditional methods. For instance, a credit card company may use abnormality detection to flag transactions that are outside of a customer's usual spending habits.
Access Control is a security measure designed to regulate who can access a compu… #
In the context of fraud detection, access control is essential to prevent unauthorized access to sensitive data and systems. Related terms include Authentication and Authorization. Access control can be implemented through various methods, such as passwords, biometric authentication, and role-based access control. For example, a company may implement access control to restrict access to sensitive financial data to only authorized personnel.
Account Takeover refers to the act of an unauthorized individual gaining access… #
Related terms include Identity theft and Account compromise. Account takeover is a serious threat to individuals and organizations, as it can result in financial loss, damage to reputation, and compromised sensitive data. For instance, a hacker may use phishing to gain access to a user's online banking account and transfer funds to an unauthorized account.
Advanced Persistent Threats (APT) refer to sophisticated, targeted attacks on co… #
Related terms include Malware and Zero-day exploits. APTs are designed to evade detection and persist on a network for an extended period, often to steal sensitive data or disrupt operations. For example, a nation-state actor may use APTs to steal sensitive intellectual property from a company.
Anomaly Detection is the process of identifying patterns or behaviors that are o… #
Related terms include Abnormality detection and Outlier analysis. Anomaly detection is crucial in fraud detection as it helps to identify potential threats that may have gone unnoticed by traditional methods. For instance, a credit card company may use anomaly detection to flag transactions that are outside of a customer's usual spending habits.
Artificial Intelligence (AI) refers to the development of computer systems that… #
Related terms include Machine learning and Deep learning. AI is increasingly being used in fraud detection to analyze patterns, identify anomalies, and predict potential threats. For example, a company may use AI-powered systems to analyze customer behavior and flag suspicious transactions.
Asset Protection refers to the measures taken to protect an organization's asset… #
Related terms include Risk management and Compliance. Asset protection is essential in fraud detection as it helps to prevent financial loss, damage to reputation, and compromised sensitive data. For instance, a company may implement asset protection measures to restrict access to sensitive data and systems.
Authentication refers to the process of verifying the identity of a user, device… #
Related terms include Authorization and Access control. Authentication is crucial in fraud detection as it helps to prevent unauthorized access to sensitive data and systems. For example, a company may implement two-factor authentication to verify the identity of users accessing sensitive systems.
Authorization refers to the process of granting access to a user, device, or sys… #
Related terms include Access control and Role-based access control. Authorization is essential in fraud detection as it helps to prevent unauthorized access to sensitive data and systems. For instance, a company may implement authorization measures to restrict access to sensitive financial data to only authorized personnel.
Behavioral Biometrics refers to the analysis of human behavior, such as keystrok… #
Related terms include Biometric authentication and Machine learning. Behavioral biometrics is increasingly being used in fraud detection to analyze patterns and identify anomalies. For example, a company may use behavioral biometrics to analyze customer behavior and flag suspicious transactions.
Botnet refers to a network of compromised devices, often used to conduct distrib… #
Related terms include Malware and DDoS attacks. Botnets are a serious threat to individuals and organizations, as they can result in financial loss, damage to reputation, and compromised sensitive data. For instance, a hacker may use a botnet to conduct a DDoS attack on a company's website.
Card Verification Value (CVV) refers to the three #
or four-digit code on the back of a credit or debit card, used to verify the card's authenticity and prevent unauthorized transactions. Related terms include Card security code and Transaction verification. CVV is an essential security measure in fraud detection as it helps to prevent unauthorized transactions and protect sensitive data. For example, a company may require customers to enter their CVV code when making online transactions.
Cloud Security refers to the measures taken to protect cloud #
based systems, data, and applications from unauthorized access, theft, or damage. Related terms include Cloud computing and Cloud storage. Cloud security is essential in fraud detection as it helps to prevent financial loss, damage to reputation, and compromised sensitive data. For instance, a company may implement cloud security measures to restrict access to sensitive data and systems.
Compliance refers to the adherence to laws, regulations, and standards, often re… #
Related terms include Risk management and Regulatory requirements. Compliance is crucial in fraud detection as it helps to prevent financial loss, damage to reputation, and compromised sensitive data. For example, a company may implement compliance measures to adhere to data protection regulations and prevent data breaches.
Credential Stuffing refers to the act of using compromised login credentials to… #
Related terms include Phishing and Password cracking. Credential stuffing is a serious threat to individuals and organizations, as it can result in financial loss, damage to reputation, and compromised sensitive data. For instance, a hacker may use credential stuffing to gain access to a user's online banking account.
Cybersecurity refers to the measures taken to protect computer systems, networks… #
Related terms include Cyber threats and Information security. Cybersecurity is essential in fraud detection as it helps to prevent financial loss, damage to reputation, and compromised sensitive data. For example, a company may implement cybersecurity measures to restrict access to sensitive data and systems.
Data Analytics refers to the process of analyzing data to identify patterns, tre… #
Related terms include Data mining and Predictive analytics. Data analytics is crucial in fraud detection as it helps to identify potential threats and prevent financial loss. For instance, a company may use data analytics to analyze customer behavior and flag suspicious transactions.
Data Encryption refers to the process of converting plaintext data into unreadab… #
Related terms include Data protection and Encryption algorithms. Data encryption is essential in fraud detection as it helps to prevent unauthorized access to sensitive data and protect it from theft or damage. For example, a company may use data encryption to protect sensitive financial data.
Data Loss Prevention (DLP) refers to the measures taken to prevent sensitive dat… #
Related terms include Data protection and Information security. DLP is crucial in fraud detection as it helps to prevent financial loss, damage to reputation, and compromised sensitive data. For instance, a company may implement DLP measures to restrict access to sensitive data and systems.
Data Mining refers to the process of analyzing large datasets to identify patter… #
Related terms include Data analytics and Predictive analytics. Data mining is essential in fraud detection as it helps to identify potential threats and prevent financial loss. For example, a company may use data mining to analyze customer behavior and flag suspicious transactions.
Deep Learning refers to a type of machine learning that uses neural networks to… #
Related terms include Machine learning and Artificial intelligence. Deep learning is increasingly being used in fraud detection to analyze patterns and identify anomalies. For instance, a company may use deep learning to analyze customer behavior and flag suspicious transactions.
Device Fingerprinting refers to the process of collecting information about a de… #
Related terms include Device profiling and Behavioral biometrics. Device fingerprinting is essential in fraud detection as it helps to prevent unauthorized access to sensitive data and systems. For example, a company may use device fingerprinting to verify the identity of devices accessing sensitive systems.
Digital Forensics refers to the process of analyzing digital evidence, such as l… #
Related terms include Incident response and Threat intelligence. Digital forensics is crucial in fraud detection as it helps to investigate and prosecute cybercrimes. For instance, a company may use digital forensics to investigate a data breach and identify the source of the attack.
Electronic Funds Transfer (EFT) refers to the transfer of funds from one account… #
Related terms include Payment processing and Transaction verification. EFT is a common target for fraudsters, as it can result in financial loss and damage to reputation. For example, a hacker may use EFT to transfer funds from a user's account to an unauthorized account.
Encryption refers to the process of converting plaintext data into unreadable ci… #
Related terms include Data protection and Encryption algorithms. Encryption is essential in fraud detection as it helps to prevent unauthorized access to sensitive data and protect it from theft or damage. For instance, a company may use encryption to protect sensitive financial data.
Fraud Detection refers to the process of identifying and preventing fraudulent a… #
Related terms include Fraud prevention and Risk management. Fraud detection is crucial in preventing financial loss, damage to reputation, and compromised sensitive data. For example, a company may use fraud detection systems to analyze customer behavior and flag suspicious transactions.
Identity Theft refers to the act of stealing or manipulating someone's identity,… #
Related terms include Identity verification and Account takeover. Identity theft is a serious threat to individuals and organizations, as it can result in financial loss, damage to reputation, and compromised sensitive data. For instance, a hacker may use identity theft to gain access to a user's online banking account.
Incident Response refers to the process of responding to and managing cybercrime… #
Related terms include Threat intelligence and Digital forensics. Incident response is crucial in fraud detection as it helps to investigate and prosecute cybercrimes. For example, a company may use incident response to investigate a data breach and identify the source of the attack.
Information Security refers to the measures taken to protect information from un… #
Related terms include Data protection and Cybersecurity. Information security is essential in fraud detection as it helps to prevent financial loss, damage to reputation, and compromised sensitive data. For instance, a company may implement information security measures to restrict access to sensitive data and systems.
Insider Threat refers to the threat posed by authorized personnel, such as emplo… #
Related terms include Insider risk and Access control. Insider threat is a serious threat to individuals and organizations, as it can result in financial loss, damage to reputation, and compromised sensitive data. For example, an employee may intentionally compromise sensitive data to gain financially.
Machine Learning refers to the development of computer systems that can learn an… #
Related terms include Artificial intelligence and Deep learning. Machine learning is increasingly being used in fraud detection to analyze patterns and identify anomalies. For instance, a company may use machine learning to analyze customer behavior and flag suspicious transactions.
Malware refers to malicious software, such as viruses, Trojans, and other types… #
Related terms include Virus and Trojan horse. Malware is a serious threat to individuals and organizations, as it can result in financial loss, damage to reputation, and compromised sensitive data. For example, a hacker may use malware to steal sensitive data or disrupt operations.
Network Security refers to the measures taken to protect computer networks from… #
Related terms include Network architecture and Cybersecurity. Network security is essential in fraud detection as it helps to prevent financial loss, damage to reputation, and compromised sensitive data. For instance, a company may implement network security measures to restrict access to sensitive data and systems.
Outlier Detection refers to the process of identifying patterns or behaviors tha… #
Related terms include Anomaly detection and Abnormality detection. Outlier detection is crucial in fraud detection as it helps to identify potential threats that may have gone unnoticed by traditional methods. For example, a credit card company may use outlier detection to flag transactions that are outside of a customer's usual spending habits.
Payment Card Industry Data Security Standard (PCI DSS) refers to a set of securi… #
Related terms include Payment card security and Data protection. PCI DSS is essential in fraud detection as it helps to prevent unauthorized access to sensitive payment card data and protect it from theft or damage. For instance, a company may implement PCI DSS to protect sensitive payment card data.
Phishing refers to the act of attempting to obtain sensitive information, such a… #
Related terms include Social engineering and Identity theft. Phishing is a serious threat to individuals and organizations, as it can result in financial loss, damage to reputation, and compromised sensitive data. For example, a hacker may use phishing to steal sensitive data or gain access to a user's online banking account.
Predictive Analytics refers to the use of statistical models and machine learnin… #
Related terms include Data analytics and Machine learning. Predictive analytics is essential in fraud detection as it helps to identify potential threats and prevent financial loss. For instance, a company may use predictive analytics to analyze customer behavior and flag suspicious transactions.
Risk Management refers to the process of identifying, assessing, and mitigating… #
Related terms include Risk assessment and Compliance. Risk management is crucial in fraud detection as it helps to prevent financial loss, damage to reputation, and compromised sensitive data. For example, a company may implement risk management measures to restrict access to sensitive data and systems.
Role #
Based Access Control (RBAC) refers to a security approach that restricts access to sensitive data and systems based on a user's role or permissions. Related terms include Access control and Authorization. RBAC is essential in fraud detection as it helps to prevent unauthorized access to sensitive data and systems. For instance, a company may implement RBAC to restrict access to sensitive financial data to only authorized personnel.
Security Information and Event Management (SIEM) refers to a system that monitor… #
Related terms include Log analysis and Threat intelligence. SIEM is crucial in fraud detection as it helps to identify potential threats and prevent financial loss. For example, a company may use SIEM to analyze security-related data and flag suspicious activities.
Social Engineering refers to the act of manipulating individuals into divulging… #
Related terms include Phishing and Identity theft. Social engineering is a serious threat to individuals and organizations, as it can result in financial loss, damage to reputation, and compromised sensitive data. For instance, a hacker may use social engineering to steal sensitive data or gain access to a user's online banking account.
Threat Intelligence refers to the process of gathering and analyzing information… #
Related terms include Threat analysis and Cyber threats. Threat intelligence is essential in fraud detection as it helps to identify potential threats and prevent financial loss. For example, a company may use threat intelligence to analyze security-related data and flag suspicious activities.
Transaction Verification refers to the process of verifying the authenticity of… #
Related terms include Payment processing and Card verification. Transaction verification is crucial in fraud detection as it helps to prevent unauthorized transactions and protect sensitive data. For instance, a company may use transaction verification to verify the authenticity of online transactions.
Two #
Factor Authentication (2FA) refers to a security approach that requires a user to provide two forms of verification, such as a password and a code sent to their phone, to access a system or data. Related terms include Authentication and Access control. 2FA is essential in fraud detection as it helps to prevent unauthorized access to sensitive data and systems. For example, a company may implement 2FA to verify the identity of users accessing sensitive systems.
User Entity Behavior Analytics (UEBA) refers to the process of analyzing user be… #
Related terms include Behavioral biometrics and Machine learning. UEBA is increasingly being used in fraud detection to analyze patterns and identify anomalies. For instance, a company may use UEBA to analyze user behavior and flag suspicious activities.
Virus refers to a type of malware that replicates itself by attaching to other p… #
Related terms include Malware and Trojan horse. Virus is a serious threat to individuals and organizations, as it can result in financial loss, damage to reputation, and compromised sensitive data. For example, a hacker may use a virus to steal sensitive data or disrupt operations.
Whitelisting refers to the process of allowing only authorized applications, fil… #
Related terms include Blacklisting and Access control. Whitelisting is essential in fraud detection as it helps to prevent unauthorized access to sensitive data and systems. For instance, a company may implement whitelisting to restrict access to sensitive financial data to only authorized applications or users.