Reversible privacy preserving data mining: a combination of difference expansion and privacy preserving

Privacy Preserving Data Mining (PPDM) can prevent private data from disclosure in data mining. However, the current PPDM methods damaged the values of original data where knowledge from the mined data cannot be verified from the original data. In this paper, we combine the concept and technique based on the reversible data hiding to propose the reversible privacy preserving data mining scheme in order to solve the irrecoverable problem of PPDM. In the proposed privacy difference expansion (PDE) method, the original data is perturbed and embedded with a fragile watermark to accomplish privacy preserving and data integrity of mined data and to also recover the original data. Experimental tests are performed on classification accuracy, probabilistic information loss, and privacy disclosure risk used to evaluate the efficiency of PDE for privacy preserving and knowledge verification.     

Software auditing: More than a chore

Software auditing is more than simply a security measure for companies to ensure that they are operating within the law. Auditing is also a good way for them to reduce costs.     

KPS: a Web information mining algorithm

The Web mostly contains semi-structured information. It is, however, not easy to search and extract structural data hidden in a Web page. Current practices address this problem by (1) syntax analysis (i.e. HTML tags); or (2) wrappers or user-defined declarative languages. The former is only suitable for highly structured Web sites and the latter is time-consuming and offers low scalability. Wrappers could handle tens, but certainly not thousands, of information sources. In this paper, we present a novel information mining algorithm, namely KPS, over semi-structured information on the Web. KPS employs keywords, patterns and/or samples to mine the desired information. Experimental results show that KPS is more efficient than existing Web extracting methods.     

CryptoCT: towards privacy preserving color transfer and storage over cloud

Multimedia Tools and Applications - Current trend toward cloud computing coupled with emerging technologies such as high definition images/videos and 360-degree videos, has led the requirement of...     

Functional and embedded dependency inference: a data mining point of view

The issue of discovering functional dependencies from populated databases has received a great deal of attention because it is a key concern in database analysis. Such a capability is strongly required in database administration and design while being of great interest in other application fields such as query folding. Investigated for long years, the issue has been recently addressed in a novel and more efficient way by applying principles of data mining algorithms. The two algorithms fitting in such a trend are TANE and Dep-Miner. They strongly improve previous proposals. In this paper, we propose a new approach adopting a data mining point of view. We define a novel characterization of minimal functional dependencies. This formal framework is sound and simpler than related work. We introduce the new concept of free set for capturing source of functional dependencies. By using the concepts of closure and quasi-closure of attribute sets, targets of such dependencies are characterized. Our approach is enforced through the algorithm FUN which is particularly efficient since it is comparable or improves the two best operational solutions (according to our knowledge): TANE and Dep-Miner. It makes use of various optimization techniques and it can work on very large databases. Applying on real life or synthetic data more or less correlated, comparative experiments are performed in order to assess performance of FUN against TANE and Dep-Miner. Moreover, our approach also exhibits (without significant additional execution time) embedded functional dependencies, i.e. dependencies captured in any subset of the attribute set originally considered. Embedded dependencies capture a knowledge specially relevant in all fields where materialized data sets are managed (e.g. materialized views widely used in data warehouses).     

Guided perturbation: towards private and accurate mining

There have been two methods for privacy- preserving data mining: the perturbation approach and the cryptographic approach. The perturbation approach is typically very efficient, but it suffers from a tradeoff between accuracy and privacy. In contrast, the cryptographic approach usually maintains accuracy, but it is more expensive in computation and communication overhead. We propose a novel perturbation method, called guided perturbation. Specifically, we focus on a central problem of privacy-preserving data mining—the secure scalar product problem of vertically partitioned data, and give a solution based on guided perturbation, with good, provable privacy guarantee. Our solution achieves accuracy comparable to the cryptographic solutions, while keeping the efficiency of perturbation solutions. Our experimental results show that it can be more than one hundred times faster than a typical cryptographic solution.     

Togetherness and respect: ethical concerns of privacy in Global Web Societies

Today’s computer network technologies are sociologically founded on hunter-gatherer principles; common users may be possible subjects of surveillance and sophisticated internet-based attacks are almost impossible to prevent. At the same time, information and communication technology, ICT offers the technical possibility of embedded privacy protection. Making technology legitimate by design is a part of the intentional design for democracy. This means incorporating options for socially acceptable behaviour in technical systems, and making the basic principles of privacy protection, rights and responsibilities, transparent to the user. The current global e-polis already has, by means of different technologies, de facto built-in policies that define the level of user-privacy protection. That which remains is to make their ethical implications explicit and understandable to citizens of the global village through interdisciplinary disclosive ethical methods, and to make them correspond to the high ethical norms that support trust, the essential precondition of any socialization. The good news is that research along these lines is already in progress. Hopefully, this will result in a future standard approach to the privacy of network communications.

Location privacy models in mobile applications: conceptual view and research directions

Location privacy in mobile, location-aware applications is a prominent research topic spanning across different disciplines and with strong societal implications and expectations. The tumultuous growth of the mobile applications market over the past few years has however hindered the development of a systematic organization and classification of location privacy concepts. In this paper we focus on one of the key concepts, i.e. location privacy metric. We survey existing approaches to the measurement of location privacy and propose a classification framework. The notion of location privacy metric, however, cannot be fully understood without describing the context in which these metrics are used. To that extent we elaborate on the notions of application model and privacy model. The ultimate goal is to contribute to the specification of a conceptual framework for location privacy.     

Narrative and learning with Web 2.0 technologies: towards a research agenda

Abstract   This paper investigates the impact of Web. 2.0 technologies on the ways learning can be conceived of as a narrative process within contemporary contexts, using blogs as an illustrative example. It is premised on the concept of narrative as a way in which individuals represent and organize experience in order to learn from it and make it shareable with others within social contexts. The first part of the paper offers a theoretical analysis of the role of narrative in the social construction of knowledge by the ways it enables users of Web 2.0 technologies to participate meaningfully in the exchange of experiences and ideas. The second part of the paper offers a 'situated' analysis of the narrative practices engaged with by users of blogs. A 'narrative trail' is used to provide a contextualized instance of the narrative practices which are involved. The paper concludes by examining the research issues which are raised and suggests a research agenda which is needed to explore Web 2.0 technologies as social utilities affecting knowledge production, in which the adaptation of narrative theory is a central feature.     

Web mining and privacy concerns: Some important legal issues to be consider before applying any data and information extraction technique in web-based environments

Web mining is a concept that gathers all techniques, methods and algorithms used to extract information and knowledge from data originating on the web (web data). A part of this technique aims to analyze the behavior of users in order to continuously improve both the structure and content of visited web sites. Behind this quite altruistic belief – namely, to help the user feel comfortable when they visit a site through a personalization process – there underlie a series of processing methodologies which operate at least arguably from the point of view of the users’ privacy.Thus, an important question arises; to what extent may the desire to improve the services offered through a web site infringe upon the privacy of those who visit it? The use of powerful processing tools such as those provided by web mining may threaten users’ privacy.Current legal scholarship on privacy issues suggests a flexible approach that enables the determination, within each particular context, of those behaviors that can threaten individual privacy. However, it has been observed that TIC professionals, with the purpose of formulating practical rules on this matter, have a very narrow-minded concept of privacy, primarily centered on the dichotomy between personal identifiable information (PII) and anonymous data.The aim of this paper is to adopt an integrative approach based on the distinctive attributes of web mining in order to determine which techniques and uses are harmful.     

Implementation of self-managed teams in manufacturing: More of a marathon than a sprint

During the past decade teamwork in manufacturing, as in other sectors, has become the organisational form of choice. In contrast to earlier manifestations such as autonomous workgroups some 30 years earlier, this appears to have been largely for business and production reasons rather than being directly aimed at improving the quality of work life. Taken from part of a larger study of teamworking in several different manufacturing companies this paper draws upon a retrospective analysis of cases of self-managed team implementation in UK manufacturing. Examples of good and bad practice and consequent guidance have been identified where the weight of evidence gives confidence in their general applicability. A basis for benchmarking is provided, related to preparation, implementation and maintenance of self-managed teams in manufacturing. Key gaps identified are for tools to assist in early functional analysis, leadership decisions and boundary setting, and appropriate team performance measurement and reward systems.     

Guest editorial: special issue on a decade of mining the Web

As editors of the Special Issue on a Decade of Mining the Web, we provide a brief overview of how Web mining evolved from the first Web mining workshop (WEBKDD’99) till today. We then introduce the papers of the special issue. Each of them is in a domain of Web mining research; it contains a survey of the past and a vision for the future.     

More than Just Remixing: Uptake and New Media Composition

This article turns to genre theory's recent explorations of uptake, broadly defined as the ways genres interact, as a resource for sketching a pedagogy of shuttling between genres. Using uptake, I intend to reconceptualize multimodal compositions as a means of participating in rhetorical ecologies that consist of transactions between genres instead of thinking of remixes as an end in themselves. In this article, I first define the concept of uptake in detail and discuss its use in rhetorical genre studies. After further illustrating uptake through an analysis of transactions between YouTube parodies and the 2005 German language film Downfall, I discuss existing scholarship in multimodal composition that draws on genre but not the idea of uptake in order to lay a foundation for a pedagogy that highlights the links, feedbacks, and rules that coordinate genres. My aim in the last section is to sketch possibilities for how teachers and students can deploy the concept of uptake as a rhetorical tool to strengthen their awareness of genre and multimodality. In doing this, I hope to reposition multimodal projects as beginnings or midpoints that lead to students’ emersion into public discourse rather than culminations or end goals in themselves. Integrating studies of uptake into writing curricula in this way will help students to make sophisticated rhetorical decisions in the age of media convergence.     

When privacy and utility are in harmony: towards better design of presence technologies

Presence systems are valuable in supporting workplace communication and collaboration. These systems are effective, however, only if they are widely adopted and candidly used. User perceptions of the utility of the information being shared and their comfort in sharing such information strongly impact both adoption and use. This paper describes the results of a survey of user preferences regarding comfort with and utility of sharing presence data in the workplace; the effects of sampling frequency, fidelity, and aggregation; and design implications of these results. We present new results that extend some past findings and challenge others. We contribute new insights that inform the design of workplace presence technologies to increase both the utility and adoption of these systems.     

User modelling and cognitive user support: towards structured development

Model-driven engineering approaches have turned out useful when handling different perspectives on human–computer interaction, such as user profiles and problem-domain data. Their latest flavour, Model-Driven Architecture (MDA^?), targets towards platform-independent models (PIMs) and adjacent transformation mechanisms to adapt to user needs and tasks. Although in the field of user modelling and its major application domain, namely adaptive hypermedia systems (AHS), considerable effort has been spent on adaptation towards user needs, a structured development approach could not be established so far. User-oriented application designs are highly distinctive and can hardly be compared or mapped to novel or existing developments without major re-engineering effort. This paper develops an understanding of existing capabilities of already applied user-modelling techniques from a model-based perspective. Revealing the context of user models and user modelling allows determining general concepts for representing and processing knowledge for adaptation. The obtained findings show primarily technically motivated approaches, rather than designs grounded in findings from human factors. For human-centred design, a shift is suggested towards distributed cognition as a methodological and operational frame of reference for user modelling. This could help overcome existing limitations in adaptation. The corresponding research agenda requires directions on how to map psychological constructs to user-model elements and adaptable user-interface elements, such as mapping field dependence to content annotation features, in a transparent and empirically grounded way.