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T-closeness
''t''-closeness is a further refinement of ''l''-diversity group based anonymization that is used to preserve privacy in data sets by reducing the granularity of a data representation. This reduction is a trade off that results in some loss of effectiveness of data management or data mining algorithms in order to gain some privacy. The ''t''-closeness model extends the ''l''-diversity model by treating the values of an attribute distinctly by taking into account the distribution of data values for that attribute. Formal definition Given the existence of data breaches where sensitive attributes may be inferred based upon the distribution of values for ''l''-diverse data, the ''t''-closeness method was created to further ''l''-diversity by additionally maintaining the distribution of sensitive fields. The original paper by Ninghui Li, Tiancheng Li, and Suresh Venkatasubramanian defines ''t''-closeness as: Charu Aggarwal and Philip S. Yu further state in their book on privac ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Suresh Venkatasubramanian
Suresh Venkatasubramanian is an Indian computer scientist and professor at Brown University. In 2021, Prof. Venkatasubramanian was appointed to the White House Office of Science and Technology Policy, advising on matters relating to fairness and bias in tech systems. He was formerly a professor at the University of Utah. He is known for his contributions in computational geometry and differential privacy, and his work has been covered by news outlets such as Science Friday, NBC News, and Gizmodo. He also runs the Geomblog', which has received coverage from the New York Times, Hacker News, KDnuggets and other media outlets. He has served as associate editor of the ''International Journal of Computational Geometry and Applications'' and as the academic editor of '' PeerJ Computer Science'', and on program committees for the IEEE International Conference on Data Mining, the SIAM Conference on Data Mining, NIPS, SIGKDD, SODA, and STACS. Career Suresh Venkatasubramanian attended th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
L-diversity
''l''-diversity, also written as ''ℓ''-diversity, is a form of group based anonymization that is used to preserve privacy in data sets by reducing the granularity of a data representation. This reduction is a trade off that results in some loss of effectiveness of data management or Data mining, mining algorithms in order to gain some privacy. The ''l''-diversity model is an extension of the k-anonymity, ''k''-anonymity model which reduces the granularity of data representation using techniques including generalization and suppression such that any given record maps onto at least ''k-1'' other records in the data. The ''l''-diversity model handles some of the weaknesses in the ''k''-anonymity model where protected identities to the level of ''k''-individuals is not equivalent to protecting the corresponding sensitive values that were generalized or suppressed, especially when the sensitive values within a group exhibit homogeneity. The ''l''-diversity model adds the promotion of in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
K-anonymity
''k''-anonymity is a property possessed by certain anonymized data. The concept of ''k''-anonymity was first introduced by Latanya Sweeney and Pierangela Samarati in a paper published in 1998 as an attempt to solve the problem: "Given person-specific field-structured data, produce a release of the data with scientific guarantees that the individuals who are the subjects of the data cannot be re-identified while the data remain practically useful." A release of data is said to have the ''k''-anonymity property if the information for each person contained in the release cannot be distinguished from at least k - 1 individuals whose information also appear in the release. Unfortunately, the guarantees provided by k-anonymity are aspirational, not mathematical. Methods for ''k''-anonymization To use k-anonymity to process a dataset so that it can be released with privacy protection, a data scientist must first examine the dataset and decide if each attribute (column) is an ''identifie ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Anonymization
Data anonymization is a type of information sanitization whose intent is privacy protection. It is the process of removing personally identifiable information from data sets, so that the people whom the data describe remain anonymous. Overview Data anonymization has been defined as a "process by which personal data is altered in such a way that a data subject can no longer be identified directly or indirectly, either by the data controller alone or in collaboration with any other party." Data anonymization may enable the transfer of information across a boundary, such as between two departments within an agency or between two agencies, while reducing the risk of unintended disclosure, and in certain environments in a manner that enables evaluation and analytics post-anonymization. In the context of medical data, anonymized data refers to data from which the patient cannot be identified by the recipient of the information. The name, address, and full postcode must be removed ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Privacy
Privacy (, ) is the ability of an individual or group to seclude themselves or information about themselves, and thereby express themselves selectively. The domain of privacy partially overlaps with security, which can include the concepts of appropriate use and protection of information. Privacy may also take the form of bodily integrity. The right not to be subjected to unsanctioned invasions of privacy by the government, corporations, or individuals is part of many countries' privacy laws, and in some cases, constitutions. The concept of universal individual privacy is a modern concept primarily associated with Western culture, particularly British and North American, and remained virtually unknown in some cultures until recent times. Now, most cultures recognize the ability of individuals to withhold certain parts of personal information from wider society. With the rise of technology, the debate regarding privacy has shifted from a bodily sense to a digital sense. As the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data
In the pursuit of knowledge, data (; ) is a collection of discrete values that convey information, describing quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures. Data may be used as variables in a computational process. Data may represent abstract ideas or concrete measurements. Data is commonly used in scientific research, economics, and in virtually every other form of human organizational activity. Examples of data sets include price indices (such as consumer price index), unemployment rates, literacy rates, and census data. In this context, data represents the raw facts and figures which can be used in such a manner in order to capture the useful information out of it. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Management
Data management comprises all disciplines related to handling data as a valuable resource. Concept The concept of data management arose in the 1980s as technology moved from sequential processing (first punched cards, then magnetic tape) to random access storage. Since it was now possible to store a discrete fact and quickly access it using random access disk technology, those suggesting that data management was more important than business process management used arguments such as "a customer's home address is stored in 75 (or some other large number) places in our computer systems." However, during this period, random access processing was not competitively fast, so those suggesting "process management" was more important than "data management" used batch processing time as their primary argument. As application software evolved into real-time, interactive usage, it became obvious that both management processes were important. If the data was not well defined, the data wo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Algorithm
In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific Computational problem, problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can perform automated deductions (referred to as automated reasoning) and use mathematical and logical tests to divert the code execution through various routes (referred to as automated decision-making). Using human characteristics as descriptors of machines in metaphorical ways was already practiced by Alan Turing with terms such as "memory", "search" and "stimulus". In contrast, a Heuristic (computer science), heuristic is an approach to problem solving that may not be fully specified or may not guarantee correct or optimal results, especially in problem domains where there is no well-defined correct or optimal result. As an effective method, an algorithm ca ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Breach
A data breach is a security violation, in which sensitive, protected or confidential data is copied, transmitted, viewed, stolen or used by an individual unauthorized to do so. Other terms are unintentional information disclosure, data leak, information leakage and data spill. Incidents range from concerted attacks by individuals who hack for personal gain or malice ( black hats), organized crime, political activists or national governments, to poorly configured system security or careless disposal of used computer equipment or data storage media. Leaked information can range from matters compromising national security, to information on actions which a government or official considers embarrassing and wants to conceal. A deliberate data breach by a person privy to the information, typically for political purposes, is more often described as a "leak". Data breaches may involve financial information such as credit card and debit card details, bank details, personal health info ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Philip S
Philip, also Phillip, is a male given name, derived from the Greek (''Philippos'', lit. "horse-loving" or "fond of horses"), from a compound of (''philos'', "dear", "loved", "loving") and (''hippos'', "horse"). Prominent Philips who popularized the name include kings of Macedonia and one of the apostles of early Christianity. ''Philip'' has many alternative spellings. One derivation often used as a surname is Phillips. It was also found during ancient Greek times with two Ps as Philippides and Philippos. It has many diminutive (or even hypocoristic) forms including Phil, Philly, Lip, Pip, Pep or Peps. There are also feminine forms such as Philippine and Philippa. Antiquity Kings of Macedon * Philip I of Macedon * Philip II of Macedon, father of Alexander the Great * Philip III of Macedon, half-brother of Alexander the Great * Philip IV of Macedon * Philip V of Macedon New Testament * Philip the Apostle * Philip the Evangelist Others * Philippus of Croton (c. 6th centur ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Differential Privacy
Differential privacy (DP) is a system for publicly sharing information about a dataset by describing the patterns of groups within the dataset while withholding information about individuals in the dataset. The idea behind differential privacy is that if the effect of making an arbitrary single substitution in the database is small enough, the query result cannot be used to infer much about any single individual, and therefore provides privacy. Another way to describe differential privacy is as a constraint on the algorithms used to publish aggregate information about a statistical database which limits the disclosure of private information of records whose information is in the database. For example, differentially private algorithms are used by some government agencies to publish demographic information or other statistical aggregates while ensuring confidentiality of survey responses, and by companies to collect information about user behavior while controlling what is visible ev ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
