Data mining is the extraction of vast interesting patterns or knowledge from huge amount of data. The initial idea of privacy-preserving data mining PPDM was to extend traditional data mining techniques to work with the data modified to mask sensitive information. The key issues were how to modify the data and how to recover the data mining result from the modified data. Privacy-preserving data mining considers the problem of running data mining algorithms on confidential data that is not supposed to be revealed even to the party running the algorithm. In contrast, privacy-preserving data publishing (PPDP) may not necessarily be tied to a specific data mining task, and the data mining task may be unknown at the time of data publishing. PPDP studies how to transform raw data into a version that is immunized against privacy attacks but that still supports effective data mining tasks. Privacy-preserving for both data mining (PPDM) and data publishing (PPDP) has become increasingly popular because it allows sharing of privacy sensitive data for analysis purposes. One well studied approach is the k-anonymity model[1] which in turn led to other models such as confidence bounding, l-diversity, t-closeness, (α,k)-anonymity, etc. In particular, all known mechanisms try to minimize information loss and such an attempt provides a loophole for attacks. The aim of this paper is to present a survey for most of the common attacks techniques for anonymization-based PPDM & PPDP and explain their effects on Data Privacy.
Although air traffic is continuously increasing on a global scale, the next generation of management in this field is successfully handling this expansion and improving the safety of billions of future passengers. In this paper, Automatic Dependent Surveillance-Broadcast (ADS-B) was examined, which is a primary system, unlike traditional radar. This technology allows aircraft to automatically broadcast their intentions and location; however, it faces certain threats from which it requires some manner of protection. This paper discussed some techniques to encrypt and protect ADS-B messages. Staged Identity-Based Encryption (SIBE) was the most suitable means of solving the issues, providing, as it does, a sufficient level of security for ADS-B messages. In addition, the technique has attractive characteristics, such as confidentiality, efficiency, and a high enough degree of flexibility for effective key management and frequent encryption. This last attribute distinguishes the approach and renders it more popular than its peers.
With the growth of Information Technology and the Internet, governments apply the same principles and technologies that are supporting E-business revolution, to achieve similar transformation. Security becomes necessary to protect the citizens and government information.In this paper a model has been proposed to obtain security services in the E-government based on Public Key Infrastructure (PKI). To achieve more security levels, Biometrics and Hardware token are used.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.