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Fraud detection is a knowledge-intensive activity. The main AI techniques used for fraud detection include: . Data mining to classify, cluster, and segment the data and automatically find associations and rules in the data that may signify interesting patterns, including those related to fraud.
Higher levels of fraud detection entail the use of professional judgement to interpret data. Supporters of artificial intelligence being used in financial audits have claimed that increased risks from instances of higher data interpretation can be minimized through such technologies. [ 12 ]
In the policy file, along with each file or directory there is a selection-mask that tells which attributes to ignore and which to report. For example, the selection-mask could be written to report changes in modification timestamp, number of links , size of the file, permission and modes , but ignore changes to the access timestamp.
Moreover, numerous graph-related applications are found to be closely related to the heterophily problem, e.g. graph fraud/anomaly detection, graph adversarial attacks and robustness, privacy, federated learning and point cloud segmentation, graph clustering, recommender systems, generative models, link prediction, graph classification and ...
Fraud detection deals with the identification of bank fraud, such as money laundering, credit card fraud and telecommunication fraud, which have vast domains of research and applications of machine learning. Because ensemble learning improves the robustness of the normal behavior modelling, it has been proposed as an efficient technique to ...
STRIDE is a model for identifying computer security threats [1] developed by Praerit Garg and Loren Kohnfelder at Microsoft. [2] It provides a mnemonic for security threats in six categories.
Man-in-the-browser (MITB, MitB, MIB, MiB), a form of Internet threat related to man-in-the-middle (MITM), is a proxy Trojan horse [1] that infects a web browser by taking advantage of vulnerabilities in browser security to modify web pages, modify transaction content or insert additional transactions, all in a covert fashion invisible to both the user and host web application.
Used as part of computer security, IDMEF (Intrusion Detection Message Exchange Format) is a data format used to exchange information between software enabling intrusion detection, intrusion prevention, security information collection and management systems that may need to interact with them. IDMEF messages are designed to be processed ...