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  2. Statistical disclosure control - Wikipedia

    en.wikipedia.org/wiki/Statistical_disclosure_control

    Statistical disclosure control (SDC), also known as statistical disclosure limitation (SDL) or disclosure avoidance, is a technique used in data-driven research to ensure no person or organization is identifiable from the results of an analysis of survey or administrative data, or in the release of microdata.

  3. Confidential computing - Wikipedia

    en.wikipedia.org/wiki/Confidential_computing

    Confidential computing can enable multiple parties to engage in joint analysis using confidential or regulated data inside a TEE while preserving privacy and regulatory compliance. [25] [26] In this case, all parties benefit from the shared analysis, but no party's sensitive data or confidential code is exposed to the other parties or system ...

  4. Data masking - Wikipedia

    en.wikipedia.org/wiki/Data_masking

    Data shuffling overcomes reservations about using perturbed or modified confidential data because it retains all the desirable properties of perturbation while performing better than other masking techniques in both data utility and disclosure risk. [3] Shuffling, however, has some real strengths in certain areas.

  5. Differential privacy - Wikipedia

    en.wikipedia.org/wiki/Differential_privacy

    A formal definition of ε-differential privacy. is a dataset without the privat The 2006 Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam D. Smith article [3] introduced the concept of ε-differential privacy, a mathematical definition for the privacy loss associated with any data release drawn from a statistical database. [4]

  6. Privacy-enhancing technologies - Wikipedia

    en.wikipedia.org/wiki/Privacy-enhancing_technologies

    The objective of PETs is to protect personal data and assure technology users of two key privacy points: their own information is kept confidential, and management of data protection is a priority to the organizations who hold responsibility for any PII.

  7. Data sanitization - Wikipedia

    en.wikipedia.org/wiki/Data_sanitization

    Data sanitization involves the secure and permanent erasure of sensitive data from datasets and media to guarantee that no residual data can be recovered even through extensive forensic analysis. [1] Data sanitization has a wide range of applications but is mainly used for clearing out end-of-life electronic devices or for the sharing and use ...

  8. Data Breach Security Incidents & Lessons Learned (Plus ... - AOL

    www.aol.com/lifestyle/data-breach-security...

    Data Breach Security Incidents & Lessons Learned (Plus 5 Tips for Preventing Them) A data breach is an event that exposes confidential, private, or sensitive information to unauthorized individuals.

  9. Data loss prevention software - Wikipedia

    en.wikipedia.org/wiki/Data_loss_prevention_software

    DLP includes techniques for identifying confidential or sensitive information. Sometimes confused with discovery, data identification is a process by which organizations use a DLP technology to determine what to look for. Data is classified as either structured or unstructured.