The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Mobile healthcare system integrating wearable sensing and wireless communication technologies continuously monitors the users' health status. However, the mHealth system raises a severe privacy concern as the data it collects are private information, such as heart rate and blood pressure. In this paper, we propose an efficient and privacy-preserving mHealth data release approach for the statistic...
In today's digital world, with the increase of using internet, personal data is collected with online activities for analysis or for surveillance. So there is a need of providing privacy to the personal data. In many organizations the sensitive data is shared with authorized access, but there is still disclosure of identity of persons. So privacy is a major concern. Privacy for the sensitive data...
Privacy is an increasing concern as the number of databases containing personal information grows. Differential privacy algorithms can be used to provide safe database queries through the insertion of noise. Attackers cannot recover pieces of the initial data with certainty, but this comes at the cost of data utility. Noise insertion leads to errors, and signal to noise ratio can become an issue....
Preserving the privacy of individuals while publishing their relevant data has been an important problem. Most of previous works in privacy preserving data publication focus on one time, static release of datasets. In multiple publications however, where data is published multiple times, these techniques are unable to ensure privacy of the concerned individuals as just joining either of the releases...
Privacy protection in publishing high dimensional data is a challenging problem. Surprisingly, there are very few works on this problem. Nevertheless, the latest approach proposed so far suffers two drawbacks, namely introduction of excessive information loss and dependence on a given generalization taxonomy. To address the issues, this paper proposes a taxonomy free grouping approach for anonymizing...
With the rising of data mining technology and the appearances of data stream and uncertain data technology etc, individual data, the enterprise data are possibly leaked at any moments, so the data security has become nowadays the main topic of information security. The common way to protect privacy is to use K-anonymity in data publishing. This paper will analyse comprehensively the current research...
Sender anonymity in location-based services (LBS) attempts to hide the identity of a mobile device user who sends requests to the LBS provider for services in her proximity (e.g. ??find the nearest gas station?? etc.). The goal is to keep the requester's interests private even from attackers who (via hacking or subpoenas) gain access to the request and to the locations of the mobile user and other...
The field of distributed data mining (DDM) has emerged as an active area in recent years because the key challenge in knowledge discovery is the extraction of knowledge from massive databases. Rough set theory (RST) is one of the powerful approaches in data mining, which has been demonstrated to have its usefulness in successfully solving a variety of problems. But there is almost no literature related...
The field of distributed data mining (DDM) has emerged as an active area in recent years because the key challenge in knowledge discovery is the extraction of knowledge from massive databases. Rough set theory (RST) is one of the powerful approaches in data mining, which has been demonstrated to have its usefulness in successfully solving a variety of problems. But there is almost no literature related...
Individual privacy preservation has recently become an increasingly important issue when publishing microdata for mining purpose. K-anonymity is a popular model for protecting privacy, which requires that each record in the released dataset be indistinguishable with at least (k-1) other records with respect to quasi-identifier. MDAV, an efficient k-anonymization algorithm, has been extensively investigated...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.