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  2. AOL Mail

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    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  3. Anonymity - Wikipedia

    en.wikipedia.org/wiki/Anonymity

    Anonymity is directly related to the concept of obscurantism or pseudonymity, where an artist or a group attempts to remain anonymous, for various reasons such as adding an element of mystique to themselves or their work, attempting to avoid what is known as the "cult of personality" or hero worship (in which the charisma, good looks, wealth or ...

  4. Degree of anonymity - Wikipedia

    en.wikipedia.org/wiki/Degree_of_anonymity

    Anonymity networks have been developed and many have introduced methods of proving the anonymity guarantees that are possible, originally with simple Chaum Mixes and Pool Mixes the size of the set of users was seen as the security that the system could provide to a user. This had a number of problems; intuitively if the network is international ...

  5. The New York Times anonymous publications - Wikipedia

    en.wikipedia.org/wiki/The_New_York_Times...

    Remains anonymous June 25, 2018: What My 6-Year-Old Son and I Endured in Family Detention [9] "The author wrote on the condition of anonymity because of the gang-related threats she and her family face in the United States and in El Salvador" [9] and threat of deportation, the author being an undocumented immigrant in the U.S. [1] and asylum ...

  6. AOL Mail Help - AOL Help

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    You've Got Mail!® Millions of people around the world use AOL Mail, and there are times you'll have questions about using it or want to learn more about its features. That's why AOL Mail Help is here with articles, FAQs, tutorials, our AOL virtual chat assistant and live agent support options to get your questions answered.

  7. Data anonymization - Wikipedia

    en.wikipedia.org/wiki/Data_anonymization

    De-anonymization is the reverse process in which anonymous data is cross-referenced with other data sources to re-identify the anonymous data source. [3] Generalization and perturbation are the two popular anonymization approaches for relational data. [ 4 ]

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