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What is Anonymization

Encyclopedia of Criminal Activities and the Deep Web
A process of destroying online tracks of the data that could be used to link it to its originator.
Published in Chapter:
ICTs and Sexual Exploitation of Children in Europe
László Dornfeld (Ferenc Mádl Institute of Comparative Law, Hungary)
Copyright: © 2020 |Pages: 15
DOI: 10.4018/978-1-5225-9715-5.ch038
Abstract
The development of digital information and communications technologies changed society in many ways. Many new threats, including online child pornography, emerged. Child pornography appeared with the emergence of photography, and since then, with each technological advance, there was an increase in the availability of these materials. The article focuses on how ICTs changed the production and distribution of child pornography and the European response to this new threat. As this criminal behavior targets one of the most vulnerable groups of society, and it being a global phenomenon, it is important for international organizations to combat it. For the European Union, this is one of the priorities for over one and a half decades and since then many legal, political, and institutional changes took place.
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More Results
What Can Fitness Apps Teach Us About Group Privacy?
A process of removing personally identifying information from data for the purpose of preserving the privacy of the people whom the data describe.
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Privacy Preservation in Smart Grid Environment
The process of hiding a person’s true identity.
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Ethical Considerations and Privacy Concerns in AI-Enabled Libraries
The process of removing personally identifiable information from datasets to protect privacy. Anonymizing user data helps mitigate re-identification risks when training AI algorithms.
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An Overview on Protecting User Private-Attribute Information on Social Networks
A technique to sanitize information for privacy protection by encryption or removing identifiable information.
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Big Data Security: Challenges, Recommendations and Solutions
Anonymization is the process of protecting data privacy across information systems. Several models and methods are used to implement it such as: t-closeness, m-invariance, k-anonymity and l-diversity.
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Data Protection and Data Security Regarding Grid Computing in Biomedical Research
The changing of personal data in such a way that the re-identification of the person/subject is no longer possible (absolute Ananymization) or only with large amount of time, cost and manpower possible (de facto anonymized, scientific use files).
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Using Big Data in Healthcare
The severing of links between people in a database and their records, in order to prevent the discovery of the human source of the records.
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Anonymity and Pseudonymity in Data-Driven Science
The obfuscation of the record owners’ identities.
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