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Privacy Of Data Stream Using Sliding Window Method

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Privacy Preserving In Data Stream Using Sliding Window Method

1. INTRODUCTION:
Data Mining is defined as extracting information from huge sets of data. In other words, we can say that data mining is the procedure of mining knowledge from data. There is a huge amount of data available in the Information Industry. This data is of no use until it is converted into useful information. It is necessary to analyse this huge amount of data and extract useful information from it. Extraction of information is not the only process we need to perform; data mining also involves other processes such as Data Cleaning, Data Integration, Data Transformation, Data Mining, Pattern Evaluation and Data Presentation [12].
Information is today probably the …show more content…

2.1 Anonymization based PPDM
The basic form of the data in a table consists of following four types of attributes:
(i) Explicit Identifiers is a set of attributes containing information that identifies a record owner explicitly such as name, SS number etc.
(ii) Quasi Identifiers is a set of attributes that could potentially identify a record owner when combined with publicly available data.
(iii) Sensitive Attributes is a set of attributes that contains sensitive person specific information such as disease, salary etc.
(iv) Non-Sensitive Attributes is a set of attributes that creates no problem if revealed even to untrustworthy parties [4].

Anonymization refers to an approach where identity or/and sensitive data about record owners are to be hidden. It even assumes that sensitive data should be retained for analysis. It 's obvious that explicit identifiers should be removed but still there is a danger of privacy intrusion when quasi identifiers are linked to publicly available data. Such attacks are called as linking attacks. For example attributes such as DOB, Sex, Race, and Zip are available in public records such as voter list.

Figure 1: Linking Attack
Such records are available in medical records also, when linked, can be used to infer

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