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Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
Pinpoint: Efficient And Effective Resource Isolation For Mobile Security And Privacy, Paul Ratazzi, Ashok Bommisetti, Nian Ji, Wenliang Du
Pinpoint: Efficient And Effective Resource Isolation For Mobile Security And Privacy, Paul Ratazzi, Ashok Bommisetti, Nian Ji, Wenliang Du
Electrical Engineering and Computer Science - All Scholarship
Virtualization is frequently used to isolate untrusted processes and control their access to sensitive resources. However, isolation usually carries a price in terms of less resource sharing and reduced inter-process communication. In an open architecture such as Android, this price and its impact on performance, usability, and transparency must be carefully considered. Although previous efforts in developing general-purpose isolation solutions have shown that some of these negative sideeffects can be mitigated, doing so involves overcoming significant design challenges by incorporating numerous additional platform complexities not directly related to improved security. Thus, the general purpose solutions become inefficient and burdensome if …
Privacy-Preserving Top-N Recommendation On Horizontally Partitioned Data, Huseyin Polat, Wenliang Du
Privacy-Preserving Top-N Recommendation On Horizontally Partitioned Data, Huseyin Polat, Wenliang Du
Electrical Engineering and Computer Science - All Scholarship
Collaborative filtering techniques are widely used by many E-commerce sites for recommendation purposes. Such techniques help customers by suggesting products to purchase using other users’ preferences. Today’s top-recommendation schemes are based on market basket data, which shows whether a customer bought an item or not. Data collected for recommendation purposes might be split between different parties. To provide better referrals and increase mutual advantages, such parties might want to share data. Due to privacy concerns, however, they do not want to disclose data. This paper presents a scheme for binary ratings-based top-N recommendation on horizontally partitioned data, in which two …
Privacy-Preserving Multivariate Statistical Analysis: Linear Regression And Classification, Wenliang Du, Yunghsiang S. Han, Shigang Chen
Privacy-Preserving Multivariate Statistical Analysis: Linear Regression And Classification, Wenliang Du, Yunghsiang S. Han, Shigang Chen
Electrical Engineering and Computer Science - All Scholarship
Analysis technique that has found applications in various areas. In this paper, we study some multivariate statistical analysis methods in Secure 2-party Computation (S2C) framework illustrated by the following scenario: two parties, each having a secret data set, want to conduct the statistical analysis on their joint data, but neither party is willing to disclose its private data to the other party or any third party. The current statistical analysis techniques cannot be used directly to support this kind of computation because they require all parties to send the necessary data to a central place. In this paper, We define …
Privacy-Preserving Collaborative Filtering Using Randomized Perturbation Techniques, Huseyin Polat, Wenliang Du
Privacy-Preserving Collaborative Filtering Using Randomized Perturbation Techniques, Huseyin Polat, Wenliang Du
Electrical Engineering and Computer Science - All Scholarship
Collaborative Filtering (CF) techniques are becoming increasingly popular with the evolution of the Internet. E-commerce sites use CF systems to suggest products to customers based on like-minded customers' preferences. People use CF systems to cope with information overload. To conduct collaborative filtering, data from customers are needed. However, collecting high quality data from customers is not an easy task because many customers are so concerned about their privacy that they might decide to give false information. CF systems using these data might produce inaccurate recommendations. We propose a randomized perturbation technique to protect users' privacy while still producing accurate recommendations. …
Building Decision Tree Classifier On Private Data, Wenliang Du, Zhijun Zhan
Building Decision Tree Classifier On Private Data, Wenliang Du, Zhijun Zhan
Electrical Engineering and Computer Science - All Scholarship
This paper studies how to build a decision tree classifier under the following scenario: a database is vertically partitioned into two pieces, with one piece owned by Alice and the other piece owned by Bob. Alice and Bob want to build a decision tree classifier based on such a database, but due to the privacy constraints, neither of them wants to disclose their private pieces to the other party or to any third party. We present a protocol that allows Alice and Bob to conduct such a classifier building without having to compromise their privacy. Our protocol uses an untrusted …
A Practical Approach To Solve Secure Multi-Party Computation Problems, Wenliang Du, Zhijun Zhan
A Practical Approach To Solve Secure Multi-Party Computation Problems, Wenliang Du, Zhijun Zhan
Electrical Engineering and Computer Science - All Scholarship
Secure Multi-party Computation (SMC) problems deal with the following situation: Two (or many) parties want to jointly perform a computation. Each party needs to contribute its private input to this computation, but no party should disclose its private inputs to the other parties, or to any third party. With the proliferation of the Internet, SMC problems becomes more and more important. So far no practical solution has emerged, largely because SMC studies have been focusing on zero information disclosure, an ideal security model that is expensive to achieve. Aiming at developing practical solutions to SMC problems, we propose a new …
Privacy-Preserving Cooperative Statistical Analysis, Wenliang Du, Mikhail J. Atallah
Privacy-Preserving Cooperative Statistical Analysis, Wenliang Du, Mikhail J. Atallah
Electrical Engineering and Computer Science - All Scholarship
The growth of the Internet opens up tremendous opportunities for cooperative computation, where the answer depends on the private inputs of separate entities. Sometimes these computations may occur between mutually untrusted entities. The problem is trivial if the context allows the conduct of these computations by a trusted entity that would know the inputs from all the participants; however if the context disallows this then the techniques of secure multi-party computation become very relevant and can provide useful solutions. Statistic analysis is a widely used computation in real life, but the known methods usually require one to know the whole …
Secure Multi-Party Computation Problems And Their Applications: A Review And Open Problems, Wenliang Du, Mikhail J. Atallah
Secure Multi-Party Computation Problems And Their Applications: A Review And Open Problems, Wenliang Du, Mikhail J. Atallah
Electrical Engineering and Computer Science - All Scholarship
The growth of the Internet has triggered tremendous opportunities for cooperative computation, where people are jointly conducting computation tasks based on the private inputs they each supplies. These computations could occur between mutually untrusted parties, or even between competitors. For example, customers might send to a remote database queries that contain private information; two competing financial organizations might jointly invest in a project that must satisfy both organizations' private and valuable constraints, and so on. Today, to conduct such computations, one entity must usually know the inputs from all the participants; however if nobody can be trusted enough to know …
Formal Development Of Secure Email, Dan Zhou, Joncheng C. Kuo, Susan Older, Shiu-Kai Chin
Formal Development Of Secure Email, Dan Zhou, Joncheng C. Kuo, Susan Older, Shiu-Kai Chin
Electrical Engineering and Computer Science - All Scholarship
Developing systems that are assured to be secure requires precise and accurate descriptions of specifications, designs, implementations, and security properties. Formal specification and verification have long been recognized as giving the highest degree of assurance. In this paper, we describe a software development process that integrates formal verification and synthesis. We demonstrate this process by developing assured sender and receiver C++ code for a secure electronic mail system, Privacy Enhanced Mail. We use higher-order logic for system-requirements specification, design specifications and design verification. We use a combination of higher-order logic and category theory and tools supporting these formalisms to refine …