Privacy on the Web: an Examination of User Concerns, Technology, and Implications for Business Organizations and Individuals

Individual privacy concerns significantly affect consumer willingness to engage in electronic commerce over the Internet. This article explores privacy concerns associated with the implementation of new information technology and introduces a new concept termed the “information technology privacy cycle.” This article also examines individual privacy on the Web, including technologies employed for collecting and protecting information on the Web, and the success of legal and technical remedies. Also assessed is the future potential of technology-based solutions through a focused examination of the Platform for Privacy Preferences as well as a discussion of the practical and theoretical implications for business organizations and individuals.     

On viewing block codes as finite automata

Block codes are viewed from a formal language theoretic perspective. It is shown that properties of trellises for subclasses of block codes called rectangular codes follow naturally from the Myhill Nerode theorem. A technique termed subtrellis overlaying is introduced with the object of reducing decoder complexity. Necessary and sufficient conditions for trellis overlaying are derived from the representation of the block code as a group, partitioned into a subgroup and its cosets. The conditions turn out to be simple constraints on coset leaders. It is seen that overlayed trellises are tail-biting trellises for which decoding is generally more efficient than that for conventional trellises. Finally, a decoding algorithm for tail-biting trellises is described, and the results of some simulations are presented.     

A Branching Time Temporal Framework for Quantitative Reasoning

Temporal logics such as Computation Tree Logic (CTL) and Linear Temporal Logic (LTL) have become popular for specifying temporal properties over a wide variety of planning and verification problems. In this paper we work towards building a generalized framework for automated reasoning based on temporal logics. We present a powerful extension of CTL with first-order quantification over the set of reachable states for reasoning about extremal properties of weighted labeled transition systems in general. The proposed logic, which we call Weighted Quantified Computation Tree Logic (WQCTL), captures the essential elements common to the domain of planning and verification problems and can thereby be used as an effective specification language in both domains. We show that in spite of the rich, expressive power of the logic, we are able to evaluate WQCTL formulas in time polynomial in the size of the state space times the length of the formula. Wepresent experimental results on the WQCTL verifier.     

Moving from Weakly Endochronous Systems to Delay-Insensitive Circuits

We consider the problem of synthesizing the asynchronous wrappers and glue logic needed for the correct GALS implementation of a modular synchronous system. Our approach is based on the weakly endochronous synchronous model, which defines high-level, implementation-independent conditions guaranteeing correct desynchronization at the level of the abstract synchronous model. We can therefore factor the synthesis problem into (1) a high-level, implementation-independent phase insuring the weak endochrony of each synchronous module and (2) the actual wrapper synthesis phase, highly simplified by the high-level assumptions, yet flexible enough to produce various, efficient implementations.We focus here on the synthesis of delay-insensitive asynchronous wrappers from weakly endochronous synchronous modules, and show how this can be done for a simple DLX processor model.     

A Theoretical Analysis of Query Selection for Collaborative Filtering

We consider the problem of determining which of a set of experts has tastes most similar to a given user by asking the user questions about his likes and dislikes. We describe a simple algorithm for generating queries for a theoretical model of this problem. We show that the algorithm requires at most opt(F)(ln(|F|/opt(F)) + 1) + 1 queries to find the correct expert, where opt(F) is the optimal worst-case bound on the number of queries for learning arbitrary elements of the set of experts F. The algorithm runs in time polynomial in |F| and |X| (where X is the domain) and we prove that no polynomial-time algorithm can have a significantly better bound on the number of queries unless all problems in NP have n ^{O(log log n)} time algorithms. We also study a more general case where the user ratings come from a finite set Y and there is an integer-valued loss function on Y that is used to measure the distance between the ratings. Assuming that the loss function is a metric and that there is an expert within a distance from the user, we give a polynomial-time algorithm that is guaranteed to find such an expert after at most 2opt(F, ) ln + 2( + 1)(1 + deg(F, )) queries, where deg(F, ) is the largest number of experts in F that are within a distance 2 of any f F.     

Synthy: A system for end to end composition of web services

The demand for quickly delivering new applications is increasingly becoming a business imperative today. However, application development is often done in an ad hoc manner resulting in poor reuse of software assets and longer time-to-delivery. Web services have received much interest due to their potential in facilitating seamless business-to-business or enterprise application integration. A web service composition system can help automate the process, from specifying business process functionalities, to developing executable workflows that capture non-functional (e.g. Quality of Service (QoS)) requirements, to deploying them on a runtime infrastructure. Intuitively, web services can be viewed as software components and the process of web service composition similar to software synthesis. In addition, service composition needs to address the build-time and runtime issues of the integrated application, thereby making it a more challenging and practical problem than software synthesis. However, current solutions based on business web services (using WSDL, BPEL, SOAP, etc.) or semantic web services (using ontologies, goal-directed reasoning, etc.) are both piecemeal and insufficient. We formulate the web service composition problem and describe the first integrated system for composing web services end to end, i.e., from specification to deployment. The proposed solution is based on a novel two-staged composition approach that addresses the information modeling aspects of web services, provides support for contextual information while composing services, employs efficient decoupling of functional and non-functional requirements, and leads to improved scalability and failure handling. We also present Synthy, a prototype of the service composition system, and demonstrate its effectiveness with the help of an application scenario from the telecom domain.     

EMERS: a tree matching–based performance evaluation of mathematical expression recognition systems

Performance evaluation of mathematical expression recognition systems is attempted. The proposed method assumes expressions (input as well as recognition output) are coded following MathML or T_EX/LaT_EX (which also gets converted into MathML) format. Since any MathML representation follows a tree structure, evaluation of performance has been modeled as a tree-matching problem. The tree corresponding to the expression generated by the recognizer is compared with the groundtruthed one by comparing the corresponding Euler strings. The changes required to convert the tree corresponding to the expression generated by the recognizer into the groundtruthed one are noted. The number of changes required to make such a conversion is basically the distance between the trees. This distance gives the performance measure for the system under testing. The proposed algorithm also pinpoints the positions of the changes in the output MathML file. Testing of the proposed evaluation method considers a set of example groundtruthed expressions and their corresponding recognized results produced by an expression recognition system.     

Anomaly Detection Using Real-Valued Negative Selection

This paper describes a real-valued representation for the negative selection algorithm and its applications to anomaly detection. In many anomaly detection applications, only positive (normal) samples are available for training purpose. However, conventional classification algorithms need samples for all classes (e.g. normal and abnormal) during the training phase. This approach uses only normal samples to generate abnormal samples, which are used as input to a classification algorithm. This hybrid approach is compared against an anomaly detection technique that uses self-organizing maps to cluster the normal data sets (samples). Experiments are performed with different data sets and some results are reported.