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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. Deepfake - Wikipedia

    en.wikipedia.org/wiki/Deepfake

    Facebook has taken efforts towards encouraging the creation of deepfakes in order to develop state of the art deepfake detection software. Facebook was the prominent partner in hosting the Deepfake Detection Challenge (DFDC), held December 2019, to 2114 participants who generated more than 35,000 models. [214]

  5. Invidious - Wikipedia

    en.wikipedia.org/wiki/Invidious

    Invidious is a free and open-source alternative frontend to YouTube. [2] [3] It is available as a Docker container, [4] or from the GitHub master branch. [5]It is intended to be used as a lightweight and "privacy-respecting" alternative to the official YouTube website. [2]

  6. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

  7. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.

  8. 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.

  9. 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.