Table 3 - uploaded by Ken Barker
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We propose a new privacy model for XML data called Privacy for All (P4A) to capture collectors privacy practice and data providers privacy preferences. Through P4A data collectors specify the purpose of data collection along with recipients, retention time and users. Data providers can agree to the collectors’ practice or impose their own privacy p...
Contexts in source publication
Context 1
... and collectors specify access types for leaf nodes where information is stored. Table 3 depicts the proposed access codes for leaf nodes. Code No (N) means the leaf node must not be accessed while Yes (Y) allows unconditional access to it. ...
Context 2
... privacy practice (PPraM, Recipient-constraints, and User-constraints) is first queried and the answer is Q(λ, ψ, u, υ) = (a, b, ω), where a ∈ α , b ∈ β, and ω ∈ Ω. If a ∈ {R, C, Q} additional conditions are included in the query as where clauses (see Table 3) and the query becomes Q P P reM . It is next performed on PPreM if a = N with Q P P reM < λ, ω P P raM , ψ, υ >, where ω P P raM represents the conditions specified in PPraM for leaf node λ. ...
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Citations
... In the literature [13], Angela put forward a privacy model called P4A (Privacy for All) to capture collector's privacy practice and data providers' privacy preferences. In this model, a privacy policy considered two major elements: the data and the purpose of usage. is model offered more flexibility than current approaches, in that it allowed unconditional and conditional access. ...
In order to protect the sensitive data represented as XML documents in a trusted collaborative system where sensitive data are not shared, an XML privacy-preserving data disclosure decision scheme was proposed under the assumption of a trusted server. This scheme is inspired by the idea of separating storage structure and content. Temporary access matrix is used to represent structure authorization and the vector represents the content authorization of leaf node. According to the conversion rules, access matrix not only represents access authorization of all nodes but also keeps the main structure of the XML document. With the combination of the vector and matrix, it can provide different access views for different group users with different purposes. In addition, start-end encoding is used to encode all the nodes for locating nodes and the content; privilege matrix solves the problem of privacy synchronization change for all users. At the same time, authentication polynomials are used to verify different users and improve the security level. The experimental results show that the scheme not only effectively protects XML sensitive data but also reduces the storage pressure on the server side; at the same time, from the response time, we know that it is beneficial for the rapid search and information positioning.
... So this mechanism suffered from high maintenance and storage costs especially for a large number of users. Angela et al. [22] put forward a privacy model called Privacy for All (P4A). In this model, a privacy policy considered two major elements: Data and the purpose of use. ...
With XML becoming a promising standard for data storage, describing, transferring and exchanging information on the Internet, data security and privacy protection of XML become the focus of research in recent years. In order to achieve the authorization of legitimate user and ensure the secure access to sensitive information, in this paper, in the context of cloud storage, with the purpose of sharing sensitive XML information, a polynomial authorization scheme with Kerberos authentication was proposed, which was based on the users' access purpose and privacy policy. In this scheme, first, Kerberos authentication was used to identify the user, and then the polynomial whose coefficients were from the leaf node address was used to complete the authorization of user. For the legitimate user, under the interaction of authorization polynomials and the global structure view, authorization matrix is generated dynamically, its temporary and dynamic characteristics greatly improves the security of the system. Finally, with the help of authorization matrix and auxiliary information tables, security queries were successfully completed. The experimental results show that the scheme not only effectively protects XML sensitive data, but also reduces the server's storage pressure, at the same time it is beneficial to the rapid search and information positioning.
... The OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal Data [15] contain what is probably the most influential articulation of the principle of purpose of use of private data, by stipulating that use of data should comply with the purpose specified at or before collection time. " Purpose " has thus been included in a number of privacy-oriented access control models [3, 8, 14, 21] and in policy specification languages such as P3P [23], EPAL [20] and XACML [17] as a decision factor in the access control policy. The method by which the purpose of an Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. ...
One of the main privacy concerns of users when submitting their data to an organization is that their data will be used only for the specified purposes. Although privacy policies can specify the purpose, enforcing such policies remains a challenge. In this paper we propose an approach to enforcing purpose in access control systems that uses workflows. The intuition behind this approach is that purpose of access can be inferred, and hence associated with, the workflow in which the access takes place. We thus propose to encode purposes as properties of workflows used by organizations and show how this can be implemented. The approach is more general than other known approaches to purpose-based enforcement, and can be used to implement them. We argue the advantages of the new approach in terms of accuracy and expressiveness.
With eXtensible Markup Language (XML) becoming a ubiquitous language for data storage and transmission in various domains, effectively safeguarding the XML document containing sensitive information is a critical issue. In this study, the authors propose a new access control model with filtering privacy. Based on the idea of separating the structure and content of the XML document, they provide a method to extract the main structure of the XML document and use matrix to save the structure information, at the same time, the start-end region encoding is used to combine the corresponding structure and content skillfully. These not only save the storage space but also efficiently speed up the search and make it convenient to find the relevant elements, especially the finding of the related content. In order to evaluate the security and efficiency of this model, the security analysis and simulation experiment verify its performance in this work.
When eXtensible Markup Language (XML) becomes a widespread data representation and exchange format for Web applications, safeguarding the privacy of data represented in XML documents can be indispensable. In this paper, we propose an XML privacy protection model by separating the structure and content, and with cloud storage to save content information and Trusted Third Party (TTP) to help manage structure information. To protect data privacy more effectively, we will create different Document Type Definition (DTD) views for different users according to users' privacy practice and the provider's privacy preferences. To further speed up the process of gaining access to data we will adopt the start–end region encoding scheme to encode the nodes in XML document and DTD views. The experiment result shows that this mechanism has a good performance in space and time.
In mobile and wireless environments, clients will request for information by submitting queries to the server, which delivers the required data via point-to-point connection or broadcast channels. The broadcast paradigm possesses the advantage of scalability. However, the broadcast data is vulnerable to eavesdropping and the adversary may be able to associate the requested data items and hence the original query with a specific client, a form of privacy threat that we would like to protect against. In this paper, we propose to protect the privacy of queries generated by individual clients by allowing them to hide themselves behind other clients. We assume a possibly untrustworthy server and make use of a trustworthy anonymizer for the queries. At the query anonymizer, user queries are clustered and consolidated into subsuming queries, to obfuscate the queries from being recovered. The consolidated queries are then expanded to improve the obfuscation effect, making it harder for the adversary to deduce the original queries. We define various performance metrics on the query privacy, by studying the ability that the adversary could crack the client queries, and propose algorithms to obfuscate a collection of user queries.
