Razlinovka Kosaya Lista A4 Dlya Pervoklassnika

Write something about yourself. No need to be fancy, just an overview. No Archives Categories. Pesni-peredelki dlya KVN, kapustnikov i veselykh vecherinok (Russian) Hardcover – 2007. By Avt.-sost. Nadezhdina (Author) Be the first to review this item. See all formats and editions Hide other formats and editions. Price New from.

Razlinovka Kosaya Lista A4 Dlya Pervoklassnika

Contents • • • • Privacy-preserving technologies related terms [ ] • Adversarial capabilities – collection of actions (e.g., observations, computations, storage) that represent the assumed power of the adversary at the time of deploying an attack. • – entity that deploys attacks according to her adversarial capabilities with the goal of compromising a system and gain privileged access to sensitive information. Pro 100 545 torrent pdf.

• Anonymity – anonymity is the state of being not identifiable within a set of subjects, the anonymity set. The anonymity set is the set of all possible subjects who might cause an action.

• Anonymization – the data subject is not identifiable by all the means likely reasonably to be used either by the controller or by any other person to identify the said person. • Anonymous communication – network capable of hiding the relationships of communicating partner with respect to an adversary observing the communications. • Credit risk scoring – determination of a derived numeric expression of the level or risk associated to a customer or a credit operation. It predicts whether or not a credit extended to an applicant will likely result in profit or losses for the lending institution. A credit score is based on, among other things, a person’s past credit history. • Differential – informally, the concept of differential privacy in a dataset states that any possible outcome of an analysis should be “almost” equally likely for two datasets that differ in just one element.

Hence, the performed statistical analyses will not disclose significant information about one individual of the dataset. • Data warehouse – a collection of data within an organization primarily used for reporting and analysis to support management decision-making. A Data Warehouse often contains time-varying data integrated from different information sources. The data are usually structured, organized and accessible for business users by applying tools like online analytical processing (OLAP).

• Data mart – a repository of data that is designed to serve a particular community of knowledge workers and usually oriented to a specific business line or team. Generally, an organization’s data marts are subsets of the organization’s data warehouse. • Data controller – natural or legal person, public authority, agency or any other body which alone or jointly with others determines the purposes and means of the processing of personal data. • Data processing – any operation or set of operations which is performed upon personal data, whether or not by automatic means, such as collection, recording, organization, storage, adaptation or alteration, retrieval, consultation, use, disclosure by transmission, dissemination or otherwise making available, alignment or combination, blocking, erasure or destruction. • Data processor - natural or legal person, public authority, agency or any other body which processes personal data on behalf of the controller. • Data subject – the person about whom data is collected. • Data subject’s consent – any freely given specific and informed indication of his wishes by which the data subject signifies his agreement to the processing of personal data relating to him/her.

• Electronic Genomic Record (EGR) – all the information relative to the genetic analysis of an individual, including the raw data leading to the retrieval of such information. • Electronic Health Record (EHR) – a document maintained by each CDO the patient deals with (ANSI, 2003). • Electronic Medical Record (EMR) – legal record created, used, and maintained by the CDO with the aim of documenting, monitoring, and managing a health care delivery within the CDO. • End-to-end security – approach to security where data travelling between clients and servers’ end-points are uninterruptedly protected, even where untrusted intermediaries entities or communication channels are required.

• Enforcement mechanism – in the IT context, enforcement mechanisms are technical measures which guarantee that the execution and/or the outputs of a given system comply with some specific pre-established (security or privacy) policy. • Feared Event – an event against which the system must be protected. • Framework (privacy and security framework) – system abstraction in which tools and algorithms can be instantiated in order to provide privacy and security guarantees. • Fraud scoring – determination of the level or risk associated to a transaction. It may provide either a pass/fail response or a quantitative score reflecting the transaction’s risk. • Inference attack' – attack that allows the adversary to deduce the value of an attribute from the value of other attributes. • Metadata – data holding information about data.