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  2. Data integrity - Wikipedia

    en.wikipedia.org/wiki/Data_integrity

    An example of a data-integrity mechanism is the parent-and-child relationship of related records. If a parent record owns one or more related child records all of the referential integrity processes are handled by the database itself, which automatically ensures the accuracy and integrity of the data so that no child record can exist without a parent (also called being orphaned) and that no ...

  3. Data collection - Wikipedia

    en.wikipedia.org/wiki/Data_collection

    The main reason for maintaining data integrity is to support the observation of errors in the data collection process. Those errors may be made intentionally (deliberate falsification) or non-intentionally (random or systematic errors). [5] There are two approaches that may protect data integrity and secure scientific validity of study results: [6]

  4. Biba Model - Wikipedia

    en.wikipedia.org/wiki/Biba_model

    The Biba Model or Biba Integrity Model developed by Kenneth J. Biba in 1975, [1] is a formal state transition system of computer security policy describing a set of access control rules designed to ensure data integrity. Data and subjects are grouped into ordered levels of integrity. The model is designed so that subjects may not corrupt data ...

  5. Information technology audit - Wikipedia

    en.wikipedia.org/wiki/Information_technology_audit

    An IT audit is different from a financial statement audit.While a financial audit's purpose is to evaluate whether the financial statements present fairly, in all material respects, an entity's financial position, results of operations, and cash flows in conformity to standard accounting practices, the purposes of an IT audit is to evaluate the system's internal control design and effectiveness.

  6. Information security - Wikipedia

    en.wikipedia.org/wiki/Information_security

    Information security is the practice of protecting information by mitigating information risks. It is part of information risk management. [1] It typically involves preventing or reducing the probability of unauthorized or inappropriate access to data or the unlawful use, disclosure, disruption, deletion, corruption, modification, inspection, recording, or devaluation of information.

  7. Data quality - Wikipedia

    en.wikipedia.org/wiki/Data_quality

    Data Quality (DQ) is a niche area required for the integrity of the data management by covering gaps of data issues. This is one of the key functions that aid data governance by monitoring data to find exceptions undiscovered by current data management operations.

  8. Big data ethics - Wikipedia

    en.wikipedia.org/wiki/Big_data_ethics

    Big data ethics, also known simply as data ethics, refers to systemizing, defending, and recommending concepts of right and wrong conduct in relation to data, in particular personal data. [1] Since the dawn of the Internet the sheer quantity and quality of data has dramatically increased and is continuing to do so exponentially.

  9. Authenticated encryption - Wikipedia

    en.wikipedia.org/wiki/Authenticated_encryption

    Authenticated Encryption (AE) is an encryption scheme which simultaneously assures the data confidentiality (also known as privacy: the encrypted message is impossible to understand without the knowledge of a secret key [1]) and authenticity (in other words, it is unforgeable: [2] the encrypted message includes an authentication tag that the sender can calculate only while possessing the ...