Communication-friendly encryption of multimedia
This paper discusses encryption operations that selectively encrypt content-carrying segments of multimedia data stream. We propose and analyze three techniques that work in different domains, namely, a syntax-aware selective bitstream encryption tool with bit stuffing, a generalized index mapping encryption tool with controlled overhead and an intra-bitplane encryption tool compatible with fine granularity scalable coding. The designs of these proposed encryption operations take into consideration the inherent structure and syntax of multimedia sources and have improved friendliness to communications, compression and computation.

title: Security evaluation for communication-friendly encryption of multimedia
abstract: This paper addresses the access control issues unique to multimedia, by using a joint signal processing and cryptographic approach to multimedia encryption. Based on three atomic encryption primitives, we present a systematic study on how to strategically integrate different atomic operations to build a video encryption system. We also propose a set of multimedia-specific security metrics to quantify the security against approximation attacks and to complement the existing notion of generic data security. The resulting system can provide superior performance to both generic encryption and its simple adaptation to video in terms of a joint consideration of security, bitrate overhead, and communication friendliness.

title: Classification-based spatial error concealment for images
abstract: This paper presents a new, classification-based spatial error concealment algorithm for images. The proposed scheme takes advantage of two state-of-the-art concealment schemes and adaptively selects a better suitable concealment scheme for each corrupted block. Using a support vector machine (SVM) classifier, our proposed approach outperforms the prior art in terms of the concealment quality and has moderate computational complexity.

title: Fingerprinting Curves
abstract: This paper presents a new method for robust data hiding in curves and highlights potential applications including digital fingerprinting of map document for trace and track purposes. We parameterize a curve using the B-spline model and add a spread spectrum sequence to the coordinates of the B-spline control points. In order to achieve robust fingerprint detection, we propose an iterative alignment-minimization algorithm to perform curve registration and deal with the non-uniqueness of B-spline control points. We show through experiments the robustness of our method against various attacks such as collusion, geometric transformations and perturbation, printing-and-scanning, and some of their combinations. We demonstrate the feasibility of our method for fingerprinting topographic maps as well as writings and drawings. The extension from hiding data in 2D topographic maps to 3D elevation data sets is also discussed.

title: Data hiding in curves for collusion-resistant digital fingerprinting
abstract: This paper presents a new data hiding method for curves. The proposed algorithm parameterizes a curve using the B-spline model and adds a spread spectrum sequence in the coordinates of the B-spline control points. We demonstrate through experiments the robustness of the proposed data hiding algorithm against printing-and-scanning and collusions, and show its feasibility for collusion-resistant fingerprinting of topographic maps as well as writings/drawings from pen-based input devices.

title: Forensic analysis of nonlinear collusion attacks for multimedia fingerprinting
abstract: Digital fingerprinting is a technology for tracing the distribution of multimedia content and protecting them from unauthorized redistribution. Unique identification information is embedded into each distributed copy of multimedia signal and serves as a digital fingerprint. Collusion attack is a cost-effective attack against digital fingerprinting, where colluders combine several copies with the same content but different fingerprints to remove or attenuate the original fingerprints. In this paper, we investigate the average collusion attack and several basic nonlinear collusions on independent Gaussian fingerprints, and study their effectiveness and the impact on the perceptual quality. With unbounded Gaussian fingerprints, perceivable distortion may exist in the fingerprinted copies as well as the copies after the collusion attacks. In order to remove this perceptual distortion, we introduce bounded Gaussian-like fingerprints and study their performance under collusion attacks. We also study several commonly used detection statistics and analyze their performance under collusion attacks. We further propose a preprocessing technique of the extracted fingerprints specifically for collusion scenarios to improve the detection performance.

title: Participatory design of an orientation aid for amnesics
abstract: We present the participatory design and evaluation of an orientation aid for individuals who have anterograde amnesia. Our design team included six amnesics who have extreme difficulty storing new memories. We describe the methods we used to enable the participation of individuals with such severe cognitive impairments. Through this process, we have conceived, designed, and developed the OrientingTool, a software application for Personal Digital Assistants that can be used by amnesics to orient themselves when feeling lost or disoriented. Two complementary studies were conducted to evaluate the effectiveness of this tool in ecologically valid contexts. Our findings suggest that the OrientingTool can improve an amnesic's independence and confidence in managing situations when disoriented, and that participatory design may be productively used with participants who have significant cognitive disabilities.

title: Supporting Group-By and Pipelining in Bitmap-Enabled Query Processors
abstract: The Group-By operation is widely used in relational Data Warehouses for the aggregation and presentation of results according to user-defined criteria. Rearranging Group-By and join operations has been proposed as an optimization technique that reduces the size of the input relation. Pipelining is another optimization technique that promotes intra-query parallelism by transfering intermediate results to the next operation without materializing them. In Data Warehouses and environments in which exploratory on-line queries are common, pipelining can be used both for optimizing joins and for the reduction of response time by presenting partial results to the user. Efficient pipelining often depends on the order of the intermediate results. Order-dependent operations, such as Group-By, typically require the complete result set before ordering it, thereby making efficient pipelining impossible. In this paper we exploit bitmap indexing to implement Group-By in a manner that can be used for pipelining. Algorithms are presented for different assumptions about buffer availability and for different sort orders.

title: Encoded bitmap indexing for data warehouses
abstract: Complex query types, huge data volumes, and very high read/update ratios make the indexing techniques designed and tuned for traditional database systems unsuitable for data warehouses (DW). We propose an encoded bitmap indexing for DWs which improves the performance of known bitmap indexing in the case of large cardinality domains. A performance analysis and theorems which identify properties of good encodings for better performance are presented. We compare encoded bitmap indexing with related techniques, such as bit slicing, projection-, dynamic-, and range-based indexing.

title: Question-driven classification of retrieved documents
abstract: Many existing information access systems deliver ranked lists of documents in response to users' queries. Some systems also endeavour to represent some of the various types of relationships that can exist between documents. However, few systems provide effective mechanisms to help users discover useful information within the set of retrieved documents. In this paper, we present a question-driven approach to delivering retrieved documents in an attempt to organize them in a way that is closer to the user's mental representation of the expected answer. In our proposed approach, retrieved documents are dynamically classified into categories; an appropriate classification scheme is selected by a user on the basis of his own understanding of the information need. Experimental results show that users are more satisfied with such a directed categorization than with a list of retrieved documents.

title: Balancing productivity and consumer satisfaction for profitability: Statistical and fuzzy regression analysis
abstract: This paper examines the relationships among productivity, consumer satisfaction and profitability using the conventional statistical regression and the new fuzzy regression approaches. For service firms in the context of Hong Kong, we verify the profit hypothesis that individually both productivity and consumer satisfaction are positively linked to profitability as well as the tradeoff hypothesis that aggregately there are negative interactions between productivity and consumer satisfaction for enhancing profitability. Hence service firms should balance their efforts in productivity and consumer satisfaction, possibly by employing appropriate information technologies to improve productivity while without hurting consumer satisfaction, to optimize their profitability. The study takes advantage of the Hong Kong Consumer Satisfaction Index and deliberately focuses on total rather than partial productivity. Several models are first estimated using the ordinary least squares (OLS) method and the results generally support the two hypotheses, but the OLS approach also leaves two puzzles that estimates of the regression coefficients are: (1) not significant before considering the interactions between consumer satisfaction and productivity but significant after introducing the interaction term, and (2) significant although sample data for productivity and the interaction term are highly correlated. These puzzles, together with the observed imprecision in productivity and profitability measurements and especially the subjectivity in measuring consumer satisfaction, lead us to adopt the fuzzy linear regression (FLR) techniques to further examine the two hypotheses. The popular FLR model continues to favor our research hypotheses but fail to offer any additional insights into the examined relationships over the OLS models. We then propose a revised FLR model which, in addition to reconfirming the hypotheses, does help to explain the encountered puzzles and fuzziness, and hence suggests an encouraging methodology for marketing.