36131731
Disclosure Risk in Dynamic Two-Dimensional Contingency Tables (Extended Abstract)
Two-dimensional contingency tables are central products of many information organizations such as statistical agencies, census bureaus, and health insurance information agencies. In a contingency table, any sensitive information about individuals must be protected, while some aggregated information can be released. The disclosure risk is that the aggregated information can be used to infer some sensitive information about individuals. Since the disclosure of sensitive information may compromise privacy, confidentiality, and national interests, one needs to carefully assess the latent risk of disclosure and take effective methods to protect the data.
17592729
On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining
Additive Randomization has been a primary tool to hide sensitive private information during privacy preserving data mining. The previous work based on Spectral Filtering empirically showed that individual data can be separated from the perturbed one and as a result privacy can be seriously compromised. Our previous work initiated the theoretical study on how the estimation error varies with the noise and gave an upper bound for the Frobenius norm of reconstruction error using matrix perturbation theory. In this paper, we propose one Singular Value Decomposition (SVD) based reconstruction method and derive a lower bound for the reconstruction error. We then prove the equivalence between the Spectral Filtering based approach and the proposed SVD approach and as a result the achieved lower bound can also be considered as the lower bound of the Spectral Filtering based approach.
45088529
Chaining watermarks for detecting malicious modifications to streaming data
Abstract Authenticating streaming data is a very important research area due to its wide range of applications. Previous technologies mainly focused on authenticating data packets at the IP layer and ensuring the robustness of the verification. These schemes usually incur large communications overhead, which is not desirable in applications with limited bandwidth. In this paper, we propose a novel fragile watermarking algorithm which verifies the integrity of streaming data at the application layer. The data are divided into groups based on synchronization points, so each group can be synchronized and any modifications made to one group only affect up to two groups. A unique watermark is embedded directly into each group to save communications bandwidth. The embedded watermark can detect as well as locate any modifications made to a data stream. To ensure the completeness of the data stream, watermarks are chained across groups so that no matter how many data are deleted, these deletions can be correctly detected. Security analysis and experimental results show that the proposed scheme can efficiently detect and locate modifications and ensure the completeness of data streams.
14671442
An Approach to Outsourcing Data Mining Tasks while Protecting Business Intelligence and Customer Privacy
Data mining is playing an important role in decision making. It is beneficial to outsource data mining tasks if an organization does not have required expertise in-house. However, the organization may lose business intelligence and customer privacy during this outsourcing process. In this paper, we present a Bloom filter based solution to enable organizations to outsource their tasks of mining association rules while protecting their business intelligence and customer privacy. Our approach can achieve high precision in data mining by trading-off storage requirements
26456568
Disclosure Analysis for Two-Way Contingency Tables
Disclosure analysis in two-way contingency tables is important in categorical data analysis. The disclosure analysis concerns whether a data snooper can infer any protected cell values, which contain privacy sensitive information, from available marginal totals (i.e., row sums and column sums) in a two-way contingency table. Previous research has been targeted on this problem from various perspectives. However, there is a lack of systematic definitions on the disclosure of cell values. Also, no previous study has been focused on the distribution of the cells that are subject to various types of disclosure. In this paper, we define four types of possible disclosure based on the exact upper bound and/or the lower bound of each cell that can be computed from the marginal totals. For each type of disclosure, we discover the distribution pattern of the cells subject to disclosure. Based on the distribution patterns discovered, we can speed up the search for all cells subject to disclosure.
18397167
New Paradigm of Inference Control with Trusted Computing
The database server is a crucial bottleneck in traditional inference control architecture, as it enforces highly computation-intensive auditing for all users who query the protected database. As a result, most auditing methods, though rigorously studied, can never be implemented in practice for protecting largescale real-world database systems. To shift this paradigm, we propose a new inference control architecture that will entrust inference control to each users platform, provided that the platform is equipped with trusted computing technology. The trusted computing technology is designed to attest the state of a users platform to the database server, so as to assure the server that inference control could be enforced as expected. A generic protocol is proposed to formalize the interactions between the users platform and database server. Any existing inference control technique can work with our protocol, for which the security properties are formally proven. Since each user's platform enforces inference control for its own queries, our solution avoids the bottleneck.
2911701
Workload characterization of bioinformatics applications
The exponential growth in the amount of genomic information has spurred growing interest in large scale analysis of genetic data. Bioinformatics applications represent the increasingly important workloads. However, very few results on the behavior of these applications running on the state-of-the-art microprocessor and systems have been published. This paper proposes a suite of widely used bioinformatics applications and studies the execution characteristics of these benchmarks on a representative architecture-the Intel Pentium 4. To understand the impacts and implications of bioinformatics workloads on the microprocessor designs, we contrast the characteristics of bioinformatics workloads and the widely used SPEC 2000 integer benchmarks.
149024
Removing photography artifacts using gradient projection and flash-exposure sampling
Flash images are known to suffer from several problems: saturation of nearby objects, poor illumination of distant objects, reflections of objects strongly lit by the flash and strong highlights due to the reflection of flash itself by glossy surfaces. We propose to use a flash and no-flash (ambient) image pair to produce better flash images. We present a novel gradient projection scheme based on a gradient coherence model that allows removal of reflections and highlights from flash images. We also present a brightness-ratio based algorithm that allows us to compensate for the falloff in the flash image brightness due to depth. In several practical scenarios, the quality of flash/no-flash images may be limited in terms of dynamic range. In such cases, we advocate using several images taken under different flash intensities and exposures. We analyze the flash intensity-exposure space and propose a method for adaptively sampling this space so as to minimize the number of captured images for any given scene. We present several experimental results that demonstrate the ability of our algorithms to produce improved flash images.
14632183
Collection of network information in active networks
Collection of information about the state of the network is very important for applications both in active networks and in traditional passive networks. However, the existing methods for the collection and prediction of network state cannot meet the needs of complex and intelligent applications. Active networks provide an environment that supports the injection and execution of application-specified codes in the network nodes, and consequently suggest possibilities for the solving of such a problem. In this article we present a new method for the collection of network state information by describing how active network techniques can be used to collect this information more freely and in a user-specific way. We give also an implementation of this approach to collect network resource information and evaluate it by measurements. By using this method, users can specify both the content and the format of the network resource information that they want to acquire as well as nodes at which they want to gather these information.
16207650
Term Disambiguation in Natural Language Query for XML
Converting a natural language query sentence into a formal database query is a major challenge. We have constructed NaLIX, a natural language interface for querying XML data. Through our experience with NaLIX, we find that failures in natural language query understanding can often be dealt with as ambiguities in term meanings. These failures are typically the result of either the user's poor knowledge of the database schema or the system's lack of linguistic coverage. With automatic term expansion techniques and appropriate interactive feedback, we are able to resolve these ambiguities. In this paper, we describe our approach and present results demonstrating its effectiveness.
1293275
Getting work done on the web: supporting transactional queries
Many searches on the web have a transactional intent. We argue that pages satisfying transactional needs can be distinguished from the more common pages that have some information and links, but cannot be used to execute a transaction. Based on this hypothesis, we provide a recipe for constructing a transaction annotator. By constructing an annotator with one corpus and then demonstrating its classification performance on another,we establish its robustness. Finally, we show experimentally that a search procedure that exploits such pre-annotation greatly outperforms traditional search for retrieving transactional pages.