14335537
A Data Perturbation Approach to Privacy Protection in Data Mining
Advances in data mining techniques have raised growing concerns about privacy of personal information. Organizations that use their customers’ records in data mining activities are forced to take actions to protect the privacy of the individuals involved. A common practice for many organizations today is to remove the identity-reated attributes from customer records before releasing them to data miners or analysts. In this study, we investigate the effect of this practice and demonstrate that a majority of the records in a dataset can be uniquely identified even after identity related attributes are removed. We propose a data perturbation method that can be used by organizations to prevent such unique identification of individual records, while providing the data to analysts for data mining. The proposed method attempts to preserve the statistical properties of the data based on privacy protection parameters specified by the organization. We show that the problem can be solved in two phases, with a linear programming formulation in phase one (to preserve the marginal distribution), followed by a simple Bayes-based swapping procedure in phase two (to preserve the joint distribution). The proposed method is compared with a random perturbation method in classification performance on two real-world datasets. The results of the experiments indicate that it significantly outperforms the random method.
476243
Reconciling Attribute Values from Multiple Data Sources
Because of the heterogeneous nature of multiple data sources, data integration is often one of the most challenging tasks of today’s information systems. While the existing literature has focused on problems such as schema integration and entity identification, our current study attempts to answer a basic question: When an attribute value for a real-world entity is recorded differently in two databases, how should the “best” value be chosen from the set of possible values? We first show how probabilities for attribute values can be derived, and then propose a framework for deciding the cost-minimizing value based on the total cost of type I, type II, and misrepresentation errors.
29720896
Assessing data quality for information products
Data quality is a critical issue in the design and implementation of databases. Often, the information provided to decision-makers is derived from heterogeneous databases. To determine the quality characteristics of information provided to decision-makers (derived data), it is necessary to determine how quality characteristics associated with diverse data sources affect the quality of the derived data. We discuss a methodology to determine two data quality characteristics, accuracy and incompleteness, that are of critical importance to decision-makers. We examine how the quality metrics of source data affect metrics for data derived using relational algebra operations.
2016087
Enumeration of 9-Variable Rotation Symmetric Boolean Functions Having Nonlinearity > 240
The existence of 9-variable Boolean functions having nonlinearity strictly greater than 240 has been shown very recently (May 2006) by Kavut, Maitra and Yucel; a few functions with nonlinearity 241 have been identified by a heuristic search in the class of Rotation Symmetric Boolean Functions (RSBFs). In this paper, using combinatorial results related to the Walsh spectra of RSBFs, we efficiently perform the exhaustive search to enumerate the 9-variable RSBFs having nonlinearity > 240 and found that there are 8 ×189 many functions with nonlinearity 241 and there is no RSBF having nonlinearity > 241. We further prove that among these functions, there are only two which are different up to the affine equivalence. This is found by utilizing the binary nonsingular circulant matrices and their variants. Finally we explain the coding theoretic significance of these functions. This is the first time orphan cosets of R(1, n) having minimum weight 241 are demonstrated for n = 9. Further they provide odd weight orphans for n = 9; earlier these were known for certain n ≥11.
5653745
Foundational Certified Code in a Metalogical Framework
Foundational certified code systems seek to prove untrusted programs to be safe relative to safety policies given in terms of actual machine architectures, thereby improving the systems’ flexibility and extensibility. Previous efforts have employed a structure wherein the proofs are expressed in the same logic used to express the safety policy. We propose an alternative structure wherein safety proofs are expressed in the Twelf metalogic, thereby eliminating from those proofs an extra layer of encoding needed in the previous accounts. Using this metalogical approach, we have constructed a complete, foundational account of safety for a fully expressive typed assembly language.
1395675
Small Proof Witnesses for LF
We instrument a higher-order logic programming search procedure to generate and check small proof witnesses for the Twelf system, an implementation of the logical framework LF. In particular, we extend and generalize ideas from Necula and Rahul [16] in two main ways: 1) We consider the full fragment of LF including dependent types and higher-order terms and 2) We study the use of caching of sub-proofs to further compact proof representations. Our experimental results demonstrate that many of the restrictions in previous work can be overcome and generating and checking small witnesses within Twelf provides valuable addition to its general safety infrastructure.
19572588
Web Site Personalization Using User Profile Information
In this paper we discuss a technique for web site personalization. Connectivity analysis has been shown to be useful in identifying high quality web pages within a topic or domain specific graph of hyper linked documents. We have implemented a system that creates a view of a subset of a web site most relevant to a given user. This sort of personalization is useful for filtering a useful subset of a site so that the user gets a low volume of quality information. The essence of our approach is to augment a previous connectivity analysis with content analysis. We present an agent which assists the user when he browses and distills a personalized sub graph of the website based on his user profile.
34366805
An efficient dynamic program slicing technique
Abstract An important application of the dynamic program slicing technique is program debugging. In applications such as interactive debugging, the dynamic slicing algorithm needs to be efficient. In this context, we propose a new dynamic program slicing technique that is more efficient than the related algorithms reported in the literature. We use the program dependence graph as an intermediate program representation, and modify it by introducing the concepts of stable and unstable edges . Our algorithm is based on marking and unmarking the unstable edges as and when the dependences arise and cease during run-time. We call this algorithm edge-marking algorithm . After an execution of a node x , an unstable edge ( x , y ) is marked if the node x uses the value of the variable defined at node y . A marked unstable edge ( x , y ) is unmarked after an execution of a node z if the nodes y and z define the same variable var , and the value of var computed at the node y does not affect the present value of var defined at the node z . We show that our algorithm is more time and space efficient than the existing ones. The worst case space complexity of our algorithm is O ( n 2 ), where n is the number of statements in the program. We also briefly discuss an implementation of our algorithm.