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.
The abundance of various embedded sensors on mobile devices results in huge amount of data generation, storage requirement and also causes the encroachment into the personal privacy. But for the development of new applications or making organizational decisions, the trajectory data is to be published. Moving objects trajectory publication may result in the serious violation and a threat to the individual's...
Online Social Networks (OSNs) are becoming increasingly important in our day to day lives. Statistics show that 74% of the Internet users are involved in social networking. Unfortunately many of us are unaware of the threats and vulnerabilities that come with OSNs. These issues can be resolved by using Data Sanitization; the process of disguising sensitive information by overwriting it with realistic...
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...
This paper presents a privacy preserved face recognition framework which combines cryptographic techniques and image processing operations. Unlike other approaches, in this work, face recognition is directly applied on the encrypted data. Cryptographic keys are generated by using a random number generator based on a continuous chaotic system, which is proved to be unpredictable. One key is generated...
As a serious concern in data publishing and analysis, privacy preservation of individuals has received much attentions. Anonymity models via generalization can protect individual privacy, but often lead to superabundance information loss. Therefore, privacy preserving data publishing needs a careful balance between privacy protection and data utility. The challenge is how to lessen the information...
The increasing use of fast and efficient data mining algorithms in huge collections of personal data, facilitated through the exponential growth of technology, in particular in the field of electronic data storage media and processing power, has raised serious ethical, philosophical and legal issues related to privacy protection. To cope with these concerns, several privacy preserving methodologies...
Privacy preserving micro data publication has received wide attentions. In this paper, we investigate the randomization approach and focus on attribute disclosure under linking attacks. We give efficient solutions to determine optimal distortion parameters such that we can maximize utility preservation while still satisfying privacy requirements. We compare our randomization approach with l-diversity...
The hot demand for e-government makes it vitally important to provide a solution to privacy preservation. This paper discusses in depth the key concerns and implementation techniques related to privacy preservation in e-government, before providing a solution which best tradeoffs the demand for information disclosure and the concerns about privacy preservation.
In this era of data digitization, data mining is essential for getting valuable information. However, privacy and security issues remain major barriers during this process. Since medical records are related to human subjects, privacy protection is taken more seriously than other data mining tasks. As required by the Health Insurance Portability and Accountability Act (HIPAA), it is necessary to protect...
Research in the area of privacy preserving techniques in databases and subsequently in data mining concepts have witnessed an explosive growth-spurt in recent years. This work investigates the problem of privacy-preserving mining of frequent sequential patterns over progressive databases. We propose a procedure to protect the privacy of data by adding noisy items to each transaction. The experimental...
K-anonymity is one simple and efficient method to achieve sensitive data protected in data sharing application. The traditional k-anonymity techniques, however, have all tuples of publishing database involve in anonymity generalize which lead to reduce the precision of publishing table. This paper firstly proposes a naiumlve sensitive tuple anonymity method. In this method only sensitive tuples are...
Privacy preservation has become an important requirement in information systems that deal with personal data. In many cases this requirement is imposed by laws that recognize the right of data owners to control whom their information is shared with and the purposes for which it can be shared. Hippocratic databases have been proposed as an answer to this privacy requirement; they extend the architecture...
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...
Privacy preservation is an important issue in the release of data for mining purposes. In practical applications, data is published continuously as new data arrive. Recently, efficient anonymization for continuous data publishing has attracted much research work. However, a careful balance between privacy and utility for continuous data publishing remains an open problem. In this paper, we study the...
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...
Safeguarding patientspsila private information is one of the most challenging issues in the design and implementation of modern e-Health systems. Recent advances in Hippocratic Databases (HDB) show a promising direction towards the enforcement of privacy policies in e-Health systems. This paper tackles issues in applying the HDB design to e-Health systems. More specifically, we design an architecture...
In the E-commerce era, recommender system is introduced to share customer experience and comments. At the same time, there is a need for E-commerce entities to join their recommender system databases to enhance the reliability toward prospective customers and also to maximize the precision of target marketing. However, there will be a privacy disclosure hazard while joining recommender system databases...
Privacy preservation in data mining demands protecting both input and output privacy. The former refers to sanitizing the raw data itself before performing mining. The latter refers to preventing the mining output (model/pattern) from malicious pattern-based inference attacks. The preservation of input privacy does not necessarily lead to that of output privacy. This work studies the problem of protecting...
We study the problem of protecting privacy in the publication of location sequences. Consider a database of trajectories, corresponding to movements of people, captured by their transactions when they use credit or RFID debit cards. We show that, if such trajectories are published exactly (by only hiding the identities of persons that followed them), there is a high risk of privacy breach by adversaries...
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.