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  2. Data analysis for fraud detection - Wikipedia

    en.wikipedia.org/wiki/Data_analysis_for_fraud...

    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.

  3. Artificial intelligence in fraud detection - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence_in...

    It is widely used in the financial sector, especially by accounting firms, to help detect fraud. In 2022, PricewaterhouseCoopers reported that fraud has impacted 46% of all businesses in the world. [1] The shift from working in person to working from home has brought increased access to data.

  4. Ensemble learning - Wikipedia

    en.wikipedia.org/wiki/Ensemble_learning

    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 ...

  5. Gameover ZeuS - Wikipedia

    en.wikipedia.org/wiki/Gameover_ZeuS

    GameOver ZeuS (GOZ), also known as peer-to-peer (P2P) ZeuS, ZeuS3, and GoZeus, is a Trojan horse developed by Russian cybercriminal Evgeniy Bogachev. Created in 2011 as a successor to Jabber Zeus, another project of Bogachev's, the malware is notorious for its usage in bank fraud resulting in damages of approximately $100 million and being the main vehicle through which the CryptoLocker ...

  6. Graph neural network - Wikipedia

    en.wikipedia.org/wiki/Graph_neural_network

    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 ...

  7. Fuzzing - Wikipedia

    en.wikipedia.org/wiki/Fuzzing

    Fuzzing Project, includes tutorials, a list of security-critical open-source projects, and other resources. University of Wisconsin Fuzz Testing (the original fuzz project) Source of papers and fuzz software. Designing Inputs That Make Software Fail, conference video including fuzzy testing; Building 'Protocol Aware' Fuzzing Frameworks

  8. Credit card fraud - Wikipedia

    en.wikipedia.org/wiki/Credit_card_fraud

    A fake automated teller slot used for "skimming". Credit card fraud is an inclusive term for fraud committed using a payment card, such as a credit card or debit card. [1] The purpose may be to obtain goods or services or to make payment to another account, which is controlled by a criminal.

  9. Google hacking - Wikipedia

    en.wikipedia.org/wiki/Google_hacking

    The concept of "Google hacking" dates back to August 2002, when Chris Sullo included the "nikto_google.plugin" in the 1.20 release of the Nikto vulnerability scanner. [4] In December 2002 Johnny Long began to collect Google search queries that uncovered vulnerable systems and/or sensitive information disclosures – labeling them googleDorks.