bluuebunny/crossref_metadata_2025 huggingface dataset:
Fuzzy Approximation of DES State
Authors: González-Castolo Juan Carlos , López-Mellado Ernesto
Published: May 2011

State estimation of dynamic systems is a resort often used when only a subset of the state variables can be directly measured; observers are the entities computing the system state from the knowledge of its internal structure and its (partially) measured behaviour. The problem of discrete event systems (DES) estimation has been addressed in (Ramirez, 2003) and (Giua 2003); in these works the marking of a Petri net (PN) model of a partially observed event driven system is computed from the evolution of its inputs and outputs. The state of a system can be also inferred using the knowledge on the duration of activities. However this task becomes complex when, besides the absence of sensors, the durations of the operations are uncertain; in this situation the observer obtains and revise a belief that approximates the current system state. Consequently this approach is useful for non critical applications of state monitoring and feedback in which an approximate computation is allows. The uncertainty of activities duration in DES can be handled using fuzzy PN (FPN) (Murata, 1996), (Cardoso, 1999), (Hennequin, 2001), (Pedrycz, 2003), (Ding, 2005); this PN extension has been applied to knowledge modelling (Chen, 1990), (Koriem, 2000), (Shen, 2003), planning (Cao, 1996), reasoning (Gao, 2003) and controller design (Andreu, 1997), (Leslaw, 2004). In these works the proposed techniques include the computation of imprecise markings; however the class of models dealt does not include strongly connected PN for the modelling of cyclic behaviour. In this article we address the problem of state estimation of DES for calculating the fuzzy marking of a Fuzzy Timed Petri Net (FTPN); for this purpose a set of matrix expressions for the recursive computing the current fuzzy marking is developed. The article focuses on FTPN whose structure is a Marked Graph (called Fuzzy Timed Marked Graph -FTMG) because it allows showing intuitively the problems of the marking estimation in exhibiting cyclic behaviour.
Fuzzy Control Systems
Authors: Chen Guanrong , Hoon Joo Young
Published: May 2011

Fuzzy control systems are developed based on fuzzy set theory, attributed to Lotfi A. Zadeh (Zadeh, 1965, 1973), which extends the classical set theory with memberships of its elements described by the classical characteristic function (either “is” or “is not” a member of the set), to allow for partial membership described by a membership function (both “is” and “is not” a member of the set at the same time, with a certain degree of belonging to the set). Thus, fuzzy set theory has great capabilities and flexibilities in solving many real-world problems which classical set theory does not intend or fails to handle. Fuzzy set theory was applied to control systems theory and engineering almost immediately after its birth. Advances in modern computer technology continuously backs up the fuzzy framework for coping with engineering systems of a broad spectrum, including many control systems that are too complex or too imprecise to tackle by conventional control theories and techniques
Gene Regulation Network Use for Information Processing
Authors: Fernandez-Blanco Enrique , Serantes J. Andrés
Published: May 2011

From the unicellular to the more complex pluricellular organism needs to process the signals from its environment to survive. The computation science has already observed, that fact could be demonstrated remembering the artificial neural networks (ANN). This computation tool is based on the nervous system of the animals, but not only the nervous cells process information in an organism. Every cell has to process the development and functioning plan encoded at its DNA and every one of these cells executes this program in parallel with the others. Another interesting characteristic of natural cells is that they form systems that are tolerant to partial failures: small errors do not induce a global collapse of the system. The present work proposes a model that is based on DNA information processing, but adapting it to general information processing. This model can be based on a set of techniques called Artificial Embryogeny (Stanley K. & Miikkulainen R. 2003) which adapts characteristics from the biological cells to solve different problems.
Hierarchical Reinforcement Learning
Authors: Diuk Carlos , Littman Michael
Published: May 2011

Reinforcement learning (RL) deals with the problem of an agent that has to learn how to behave to maximize its utility by its interactions with an environment (Sutton & Barto, 1998; Kaelbling, Littman & Moore, 1996). Reinforcement learning problems are usually formalized as Markov Decision Processes (MDP), which consist of a finite set of states and a finite number of possible actions that the agent can perform. At any given point in time, the agent is in a certain state and picks an action. It can then observe the new state this action leads to, and receives a reward signal. The goal of the agent is to maximize its long-term reward. In this standard formalization, no particular structure or relationship between states is assumed. However, learning in environments with extremely large state spaces is infeasible without some form of generalization. Exploiting the underlying structure of a problem can effect generalization and has long been recognized as an important aspect in representing sequential decision tasks (Boutilier et al., 1999). Hierarchical Reinforcement Learning is the subfield of RL that deals with the discovery and/or exploitation of this underlying structure. Two main ideas come into play in hierarchical RL. The first one is to break a task into a hierarchy of smaller subtasks, each of which can be learned faster and easier than the whole problem. Subtasks can also be performed multiple times in the course of achieving the larger task, reusing accumulated knowledge and skills. The second idea is to use state abstraction within subtasks: not every task needs to be concerned with every aspect of the state space, so some states can actually be abstracted away and treated as the same for the purpose of the given subtask.
A Hybrid System for Automatic Infant Cry Recognition II
Authors: Reyes-García Carlos Alberto , Barajas Sandra E. , Tlelo-Cuautle Esteban , Reyes-Galaviz Orion Fausto
Published: May 2011

Automatic Infant Cry Recognition (AICR) process is basically a problem of pattern processing, very similar to the Automatic Speech Recognition (ASR) process (Huang, Acero, Hon, 2001). In AICR first we perform acoustical analysis, where the crying signal is analyzed to extract the more important acoustical features, like; LPC, MFCC, etc. (Cano, Escobedo and Coello, 1999). The obtained characteristics are represented by feature vectors, and each vector represents a pattern. These patterns are then classified in their corresponding pathology (Ekkel, 2002). In the reported case we are automatically classifying cries from normal, deaf and asphyxiating infants. We use a genetic algorithm to find several optimal parameters needed by the Fuzzy Relational Neural Network FRNN (Reyes, 1994), like; the number of linguistic properties, the type of membership function, the method to calculate the output and the learning rate. The whole model has been tested on several data sets for infant cry classification. The process, as well as some results, is described.
Intelligent MAS in System Engineering and Robotics
Authors: Marichal G. Nicolás , González Evelio J.
Published: May 2011

The concept of agent has been successfully used in a wide range of applications such as Robotics, e-commerce, agent-assisted user training, military transport or health-care. The origin of this concept can be located in 1977, when Carl Hewitt proposed the idea of an interactive object called actor. This actor was defined as a computational agent, which has a mail address and a behaviour (Hewitt, 1977). Actors receive messages from other actors and carry out their tasks in a concurrent way. It is difficult that a single agent could be sufficient to carry out a relatively complex task. The usual approach consists of a society of agents - called Multiagent Systems (MAS) -, which communicate and collaborate among them and they are coordinated when pursuing a goal. The purpose of this chapter is to analyze the aspects related to the application of MAS to System Engineering and Robotics, focusing on those approaches that combine MAS with other Artificial Intelligence (AI) techniques.
Knowledge Management Systems Procedural Development
Authors: Andrade Javier , Rodríguez Santiago , Seoane María , Suárez Sonia
Published: May 2011

The success of the organisations is increasingly dependant on the knowledge they have, to the detriment of other traditionally decisive factors as the work or the capital (Tissen, 2000). This situation has led the organisations to pay special attention to this new intangible item, so numerous efforts are being done in order to conserve and institutionalise it. The Knowledge Management (KM) is a recent discipline replying this increasing interest; however, and despite its importance, this discipline is currently in an immature stage, as none of the multiple existing proposals for the development of Knowledge Management Systems (KMS) achieve enough detail for perform such complex task. In order to palliate the previous situation, this work presents a methodological framework for the explicit management of the knowledge. The study has a formal basis for achieving an increased level of detail, as all the conceptually elements needed for understanding and representing the knowledge of any domain are identified. The requested descriptive character is achieved when basing the process on these elements and, in this way, the development of the systems could be guided more effectively.
Mathematical Modeling of Artificial Neural Networks
Authors: Mutihac Radu
Published: May 2011

Models and algorithms have been designed to mimic information processing and knowledge acquisition of the human brain generically called artificial or formal neural networks (ANNs), parallel distributed processing (PDP), neuromorphic or connectionist models. The term network is common today: computer networks exist, communications are referred to as networking, corporations and markets are structured in networks. The concept of ANN was initially coined as a hopeful vision of anticipating artificial intelligence (AI) synthesis by emulating the biological brain. ANNs are alternative means to symbol programming aiming to implement neural-inspired concepts in AI environments (neural computing) (Hertz, Krogh, & Palmer, 1991), whereas cognitive systems attempt to mimic the actual biological nervous systems (computational neuroscience). All conceivable neuromorphic models lie in between and supposed to be a simplified but meaningful representation of some reality. In order to establish a unifying theory of neural computing and computational neuroscience, mathematical theories should be developed along with specific methods of analysis (Amari, 1989) (Amit, 1990). The following outlines a tentatively mathematical-closed framework in neural modeling.
Modularity in Artificial Neural Networks
Authors: Téllez Ricardo , Angulo Cecilio
Published: May 2011

The concept of modularity is a main concern for the generation of artificially intelligent systems. Modularity is an ubiquitous organization principle found everywhere in natural and artificial complex systems (Callebaut, 2005). Evidences from biological and philosophical points of view (Caelli and Wen, 1999) (Fodor, 1983), indicate that modularity is a requisite for complex intelligent behaviour. Besides, from an engineering point of view, modularity seems to be the only way for the construction of complex structures. Hence, whether complex neural programs for complex agents are desired, modularity is required. This article introduces the concepts of modularity and module from a computational point of view, and how they apply to the generation of neural programs based on modules. Two levels, strategic and tactical, at which modularity can be implemented, are identified. How they work and how they can be combined for the generation of a completely modular controller for a neural network based agent is presented.
"Narrative" Information and the NKRL Solution
Authors: Piero Zarri Gian
Published: May 2011

In a companion article of this Encyclopaedia: ‘Narrative’ Information, the Problem, we have introduced the problem of finding a complete and computationally efficient system for representing and managing ‘nonfictional narrative information’. We have stressed there the important economic value of this multimedia type of information – that concerns, e.g., corporate memory documents, news stories, normative and legal texts, medical records, intelligence messages, surveillance videos or visitor logs, actuality photos, eLearning and Cultural Heritage material, etc. We have also emphasised that the usual Computer Science tools – including those pertaining to the now very popular ‘Semantic Web’ domain, see (Bechhofer et al., 2004, Beckett, 2004) – are not really suitable for dealing with this type of information.
Randomized Hough Transform
Authors: Xu Lei , Oja Erkki
Published: May 2011

Proposed in 1962, the Hough transform (HT) has been widely applied and investigated for detecting curves, shapes, and motions in the fields of image processing and computer vision. However, the HT has several shortcomings, including high computational cost, low detection accuracy, vulnerability to noise, and possibility of missing objects. Many efforts target at solving some of the problems for decades, while the key idea remains more or less the same. Proposed in 1989 and further developed thereafter, the Randomized Hough Transform (RHT) manages to considerably overcome these shortcomings via innovations on the fundamental mechanisms, with random sampling in place of pixel scanning, converging mapping in place of diverging mapping, and dynamic storage in place of accumulation array. This article will provides an overview on advances and applications of RHT in the past one and half decades.
Stream Processing of a Neural Classifier II
Authors: Martínez-Zarzuela M. , Díaz Pernas F. J. , González Ortega D. , Díez Higuera J. F. , Antón Rodríguez M.
Published: May 2011

This article presents a real-time Fuzzy ART neural classifier for skin segmentation implemented on a Graphics Processing Unit (GPU). GPUs have evolved into powerful programmable processors, becoming increasingly used in time-dependent research fields such as dynamics simulation, database management, computer vision or image processing. GPUs are designed following a Stream Processing Model and each new generation of commodity graphics cards incorporates rather more powerful and flexible GPUs (Owens, 2005). In the last years General Purpose GPU (GPGPU) computing has established as a well-accepted application acceleration technique. The GPGPU phenomenon belongs to larger research areas: homogeneous and heterogenous multi-core computing. Research in these fields is driven by factors as the Moore’s Gap. Today’s uni-processors follow a 90/100 rule, where 90 percent of the processor is passive and 10 percent is doing active work. By contrast, multi-core processors try to follow the same general rule but with 10 percent passive and 90 percent active processors when working at full throughput. Single processor Central Processing Units (CPUs) were designed for executing general purpose programs comprised of sequential instructions operating on single data. Designers tried to optimize complex control requirements with minimum latency, thus many transistors in the chip are devoted to branch prediction, out of order execution and caching. In the article Stream Processing of a Neural Classifier I several terms and concepts related to GPGPU were introduced. A detailed description of the Fuzzy ART ANN implementation on a commodity graphics card, exploiting the GPU’s parallelism and vector capabilities, was given. In this article, the aforementioned Fuzzy ART GPU-designed implementation is configured for robust real-time skin recognition. Both learning and testing processes are done on the GPU using chrominance components in TSL (Tint, Saturation and Luminance) color space. The Fuzzy ART ANN implementation recognizes skin tone pixels at a rate of 270 fps on an NVIDIA GF7800GTX GPU.
Voltage Instability Detection Using Neural Networks
Authors: Khashman Adnan , Buruncuk Kadri , Jabr Samir
Published: May 2011

The explosive growth in decision-support systems over the past 30 years has yielded numerous “intelligent” systems that have often produced less-than-stellar results (Michalewicz Z. et al., 2005). The increasing trend in developing intelligent systems based on neural networks is attributed to their capability of learning nonlinear problems offline with selective training, which can lead to sufficiently accurate online response. Artificial neural networks have been used to solve many problems obtaining outstanding results in various application areas such as power systems. Power systems applications can benefit from such intelligent systems; particularly for voltage stabilization, where voltage instability in power distribution systems could lead to voltage collapse and thus power blackouts. This article presents an intelligent system which detects voltage instability and classifies voltage output of an assumed power distribution system (PDS) as: stable, unstable or overload. The novelty of our work is the use of voltage output images as the input patterns to the neural network for training and generalizing purposes, thus providing a faster instability detection system that simulates a trained operator controlling and monitoring the 3-phase voltage output of the simulated PDS.
Environmental Drivers of E-Business Strategies Among SMEs
Authors: Arbore Alessandro , Ordanini Andrea
Published: May 2011

In front of traditional interpretations of the digital gap based on endogenous conditions of the firms, this chapter intends to emphasize the importance that some external pressures may have on the e-business strategy of small and medium enterprises (SMEs). The environmental factors analyzed here are market position, competitive intensity, and institutional pressures. SMEs have been grouped according to their level of e-business involvement, in relation to the number of e-business solutions adopted so far. Three layers are proposed: excluded, tentative, and integrated e-business SMEs. A multinomial logistic regression was used to predict these strategies. A general conclusion is that different models seem to explain exclusion and involvement. Specifically, two factors among those analyzed reveal to be more suitable in explaining e-business exclusion. They are the size of a SME and a lack of institutional pressures to adopt. On the other hand, e-business involvement seems to be primarily prompted by a selective competitive environment and not by imitative behaviors, as in the previous case.
Ubiquitous Communication Via Residential Gateways
Authors: De Smedt Alex
Published: May 2011

This chapter focuses on the equipment in the home, providing broadband access to the users into the home, called residential gateway. The chapter shows how such a device evolves from a simple modem to an advanced gateway system that contributes to: • The access inside the home of any data on any compatible device • The ubiquity of access points for the broadband network • The ubiquity of media data in the home from remote devices • The communication of mobile handsets via the fixed network. The objective of this chapter is to give the reader a technical insight into the enabling mechanisms and technologies dealing with such functionalities. The text indicates particular technical solutions, but explanations are kept high-level in order to allow nontechnical readers to understand the basics and concepts of the solutions. A number of references show that the technical exposé is becoming a reality.
ICT Statistics for Broadband Promoting Regulatory
Authors: Korsakaite Diana , Lamanauskas Tomas
Published: May 2011

This chapter introduces the statistical analysis of a number of information and communication technologies (ICT) market indicators as a means to develop sound regulatory policies aiming to promote broadband take up. The chapter provides analysis of the concept of broadband, statistical analysis of ICT indicators, time series and cross-country series against broadband penetration, determination of conterminous factors with statistically significant influence over broadband penetration in European states, and derivation of calls for regulatory policy particular actions out of statistically significant relations. The overall aim of the chapter is to offer a way how ICT statistical data could be employed to suggest preconditions for possible practical solutions in the domain of broadband promotion and in this way to bring the rhetoric of statistics down to an operational level.
Comparing China's and India's Evolution of Broadband Internet in the Developing World
Authors: Kshetri Nir , Dholakia Nikhilesh
Published: May 2011

Telecommunications networks of India and the People’s Republic of China are among the largest in the world. The two economies have a number of areas for broadband use ripe for exploration. Broadband networks in some regions in these two economies are even more developed than in some parts of the industrialized world. There are, however, a number of reasons to believe that these two countries may exhibit distinct and varied patterns of broadband diffusion. This chapter compares and contrasts the diffusion patterns of broadband technology in the two economies. We examine factors driving broadband diffusion in the two economies in three major categories: demand and cost conditions, industry structure, and export conditions.
A Tool for Fuzzy Reasoning and Querying
Authors: Xexéo Geraldo , Braga André
Published: May 2011

We present CLOUDS, which stands for C++ Library Organizing Uncertainty in Database Systems, a tool that allows the creation of fuzzy reasoning systems over classic, nonfuzzy, relational databases. CLOUDS can be used in three flavors: CLOUDS API, a C++ API; CLOUDS-L, a compiled language; and CLOUDSQL, a fuzzy extension to SQL queries (ANSI, 1992). It was developed using the objectoriented paradigm and has an extensible architecture based on a main control system that manages different models, and runs queries and commands defined in them. As a test, it was incorporated into a geographic information system and used to analyze epidemiological data.
Relational Data,Formal Concept Analysis, and Graded Attributes
Authors: Belohlavek Radim
Published: May 2011

Formal concept analysis is a particular method of analysis of relational data. Also, formal concept analysis provides elaborate mathematical foundations for relational data. In the course of the last decade, several attempts appeared to extend formal concept analysis to data with graded (fuzzy) attributes. Among these attempts, an approach based on residuated implications plays an important role. This chapter presents an overview of foundations of formal concept analysis of data with graded attributes, with focus on the approach based on residuated implications and on its extensions and particular cases. Presented is an overview of both of the main parts of formal concept analysis, namely, concept lattices and attribute implications, and an overview of the underlying foundations and related methods. In addition to that, the chapter contains an overview of topics for future research.
Data Dependencies in Codd's Relational Model with Similarities
Authors: Belohlavek Radim , Vychodil Vilem
Published: May 2011

This chapter deals with data dependencies in Codd’s relational model of data. In particular, we deal with fuzzy logic extensions of the relational model that consist of adding similarity relations to domains and consider functional dependencies in these extensions. We present a particular extension and functional dependencies in this extension that follow the principles of fuzzy logic in a narrow sense. We present selected features and results regarding this extension. Then, we use this extension as a reference model and compare it to several other extensions proposed in the literature. We argue that following the principles of fuzzy logic in a narrow sense, the same way we can follow the principles of classical logic in the case of the ordinary Codd relational model, helps achieve transparency, versatility, conceptual clarity, and theoretical and computational tractability of the extension. We outline several topics for future research.
A Distributed Algorithm for Mining Fuzzy Association Rules in Traditional Databases
Authors: Au Wai-Ho
Published: May 2011

The mining of fuzzy association rules has been proposed in the literature recently. Many of the ensuing algorithms are developed to make use of only a single processor or machine. They can be further enhanced by taking advantage of the scalability of parallel or distributed computer systems. The increasing ability to collect data and the resulting huge data volume make the exploitation of parallel or distributed systems become more and more important to the success of fuzzy association rule mining algorithms. This chapter proposes a new distributed algorithm, called DFARM, for mining fuzzy association rules from very large databases. Unlike many existing algorithms that adopt the support-confidence framework such that an association is considered interesting if it satisfies some user-specified minimum percentage thresholds, DFARM embraces an objective measure to distinguish interesting associations from uninteresting ones. This measure is defined as a function of the difference in the actual and the expected number of tuples characterized by different linguistic variables (attributes) and linguistic terms (attribute values). Given a database, DFARM first divides it into several horizontal partitions and assigns them to different sites in a distributed system. It then has each site scan its own database partition to obtain the number of tuples characterized by different linguistic variables and linguistic terms (i.e., the local counts), and exchange the local counts with all the other sites to find the global counts. Based on the global counts, the values of the interestingness measure are computed, and the sites can uncover interesting associations. By repeating this process of counting, exchanging counts, and calculating the interestingness measure, it unveils the underlying interesting associations hidden in the data. We implemented DFARM in a distributed system and used a popular benchmark data set to evaluate its performance. The results show that it has very good size-up, speedup, and scale-up performance. We also evaluated the effectiveness of the proposed interestingness measure on two synthetic data sets. The experimental results show that it is very effective in differentiating between interesting and uninteresting associations.
Fuzzy Sequential Patterns for Quantitative Data Mining
Authors: Fiot Céline
Published: May 2011

The explosive growth of collected and stored data has generated a need for new techniques transforming these large amounts of data into useful comprehensible knowledge. Among these techniques, referred to as data mining, sequential pattern approaches handle sequence databases, extracting frequently occurring patterns related to time. Since most real-world databases consist of historical and quantitative data, some works have been done for mining the quantitative information stored within such sequence databases, uncovering fuzzy sequential patterns. In this chapter, we first introduce the various fuzzy sequential pattern approaches and the general principles they are based on. Then, we focus on a complete framework for mining fuzzy sequential patterns handling different levels of consideration of quantitative information. This framework is then applied to two real-life data sets: Web access logs and a textual database. We conclude on a discussion about future trends in fuzzy pattern mining.
A Machine Learning Approach to Data Cleaning in Databases and Data Warehouses
Authors: Shahri Hamid Haidarian
Published: May 2011

Entity resolution (also known as duplicate elimination) is an important part of the data cleaning process, especially in data integration and warehousing, where data are gathered from distributed and inconsistent sources. Learnable string similarity measures are an active area of research in the entity resolution problem. Our proposed framework builds upon our earlier work on entity resolution, in which fuzzy rules and membership functions are defined by the user. Here, we exploit neuro-fuzzy modeling for the first time to produce a unique adaptive framework for entity resolution, which automatically learns and adapts to the specific notion of similarity at a meta-level. This framework encompasses many of the previous work on trainable and domain-specific similarity measures. Employing fuzzy inference, it removes the repetitive task of hard-coding a program based on a schema, which is usually required in previous approaches. In addition, our extensible framework is very flexible for the end user. Hence, it can be utilized in the production of an intelligent tool to increase the quality and accuracy of data.
Information Systems Risk Management
Authors: Ponnam Aditya
Published: May 2011

Organizations worldwide recognize the importance of a comprehensive, continuously evolving risk assessment process, built around a solid risk strategy that properly manages internal and external threats. A comprehensive enterprise risk management strategy must ideally contribute to the protection of the organizations’ assets, operations, shareholder’s value, and customer satisfaction while meeting imposed regulatory requirements and standards. As IT represents an integral part of the process required to achieve the aforementioned objectives, managing the risks associated with the information technology infrastructure of an organization is critical. The goal of this chapter is to review the most common risks and threat agents for a typical organizations’ information technology infrastructure and to discuss how systematic risk management procedures and controls can manage and minimize these risks.
An Immune-Inspired Approach to Anomaly Detection
Authors: Twycross Jamie
Published: May 2011

The immune system provides a rich metaphor for computer security: anomaly detection that works in nature should work for machines. However, early artificial immune system approaches for computer security had only limited success. Arguably, this was due to these artificial systems being based on too simplistic a view of the immune system. We present here a second generation artificial immune system for process anomaly detection. It improves on earlier systems by having different artificial cell types that process information. Following detailed information about how to build such second generation systems, we find that communication between cells types is key to performance. Through realistic testing and validation, we show that second generation artificial immune systems are capable of anomaly detection beyond generic system policies. The chapter concludes with a discussion and outline of the next steps in this exciting area of computer security.
Memory Corruption Attacks, Defenses, and Evasions
Authors: Belletini Carlo
Published: May 2011

The chapter introduces and describes representative defense mechanisms to protect from both basic and advanced exploitation of low-level coding vulnerabilities. Exploitation of low-level coding vulnerabilities has evolved from a basic stack-based buffer overflow with code injection to highly sophisticated attack techniques. In addition, pure-data attacks were demonstrated to be as efficient as control-data attacks and quite realistic. On the other hand research on assessment of the robustness of proposed mitigation techniques revealed various weaknesses in them leading to design and implementation of evasion techniques. Most of the defensive techniques protect only from a limited set of attack techniques, thus a defense employment requires multiple complementary mitigation techniques. Furthermore, there are few mitigation techniques designed to counter pure-data attacks. In response to these limitations, current research proposes better defensive mechanisms such as pointer taintedness detection and attack data burning capable of countering any kind of control-data or pure-data attack.
Implications of FFIEC Guidance on Authentication in Electronic Banking
Authors: Gupta Manish , Lee JinKyu , Rao H. R.
Published: May 2011

The Internet has emerged as the dominant medium in enabling banking transactions. Adoption of e-banking has witnessed an unprecedented increase over the last few years. In today’s online financial services environment, authentication is the bedrock of information security. Simple password authentication is the prevailing paradigm, but its weaknesses are all too evident in today’s context. In order to address the nature of similar vulnerabilities, in October 2005, the Federal Financial Institutions Examination Council (FFIEC)—which comprises the United States’ five federal banking regulators—published joint guidance entitled Authentication in an Internet Banking Environment, recommending that financial institutions deploy security measures to reliably authenticate their online banking customers. The analysis of FFIEC guidance presented in the article are with the view to equip the reader with a glimpse of the issues involved in understanding the guidance for specific banking organization that may help towards learned and better decisions regarding compliance and improved security. The chapter will allow Information Technology managers to understand information assurance issues in e-banking in a holistic manner, and help them make recommendations and actions to ensure security of e-banking components.
A Guide to Non-Disclosure Agreements for Researchers
Authors: Witman Paul D.
Published: May 2011

This chapter provides a set of guidelines to assist information assurance and security researchers in creating, negotiating, and reviewing non-disclosure agreements, in consultation with appropriate legal counsel. It also reviews the use of non-disclosure agreements in academic research environments from multiple points of view. Active academic researchers, industry practitioners, and corporate legal counsel all provided input into the compiled guidelines. An annotated bibliography and links are provided for further review.
Data Security for Storage Area Networks
Authors: Clark Tom
Published: May 2011

Data storage is playing an increasingly visible role in securing application data in the data center. Today virtually all large enterprises and institutions worldwide have implemented networked storage infrastructures to provide high performance input/output (I/O) operations, high availability access, consolidation of storage assets, and data protection and archiving. Storage area networks (SANs) are typically based on Fibre Channel technology and are normally contained within the physical confines of the data center. The security of this physical isolation, however, has proven inadequate to safeguard data from inadvertent or malicious disruption. Both established and emerging Fibre Channel and IP standards are required to secure the storage infrastructure and protect data assets from corruption or misappropriation. This paper provides an overview of storage networking technology and the security mechanisms that have been developed to provide data integrity for data center storage infrastructures.
Critical Success Factors and Indicators to Improve Information Systems Security Management Actions
Authors: Torres Jose M.
Published: May 2011

This chapter presents an Information Systems Security Management Framework (ISSMF) which encapsulates eleven Critical Success Factors (CSFs) along with a set of 62 indicators to properly manage and track the evolution of security management models. These CSFs have been identified as the most cited key factors published in the current information security literature. The set of indicators has been strictly designed for organizations seeking simple and fast alternatives to estimate current information systems security status. Furthermore, the authors have found that current organizations, particularly small and medium size enterprises, use reactive and irresponsible security strategies due to the scarcity of human and economic resources. Therefore, this chapter approaches security from a managerial perspective allowing systems administrators, especially those with a more technical profile, to build their personal balanced security scorecard choosing the CSFs and indicators that fit best in every case.
Privacy, Societal, and Ethical Concerns in Security
Authors: Rutherfoord Rebecca H.
Published: May 2011

This chapter will deal with issues of privacy, societal, and ethical concerns in enterprise security. Security for a company is defined as protecting a company from attack. Yet, the soft side of this attack deals with protecting the privacy of those clients, vendors, and employees from invaders. Privacy of individual’s data must be considered both internally and externally. Laws protecting corporations and individuals need to be understood to keep a company from being liable for infringements of unprotected data. Companies who are not up-to-date on the laws will find themselves facing litigation in various forms. The ethical side of security is a much more nebulous area for an enterprise to deal with. Companies need to understand where ethics fits into the processes for security protection. This chapter will briefly discuss these ethical and privacy issues that an enterprise must address and processes that need to be in place.
Exploitation of Public Sector Information in Europe
Authors: Chochliouros Ioannis P. , Spiliopoulou Anastasia S. , Chochliouros Stergios P.
Published: May 2011

The gradual “penetration” of an innovative, digitally-oriented information society, in the scope of the actual convergence among telecommunications, broadcasting and information technology, create primary opportunities for access and exploitation of Public Sector Information (PSI), in the context of a fully competitive and liberalised European electronic communications market. There are now significant challenges on the scene, for improving mutual communication between public sector and private companies, thus creating chances for exploiting new opportunities, to the benefit of the broader European market(s). However, the non-existence of an appropriate legal framework governing the conditions and/or terms for the commercial use of PSI constitutes a serious drawback for any serious attempt towards evolution, and for an effective development of a European e-Communications market. Recent European regulatory-oriented policies have established and supported suitable measures and provisions, to ensure access to PSI for all interested parties and for their “free” circulation among Member States. In the context of the suggested contribution we examine current European harmonization regulatory measures, towards creating transparency and legal security for all market players involved in the wider content market, thus contributing to growth.
Information Technology Among U.S. Local Governments
Authors: Norris Donald F.
Published: May 2011

The purpose of this chapter is to provide an overview of the adoption, uses, and impacts of information technology (IT), including electronic government, among local governments in the United States1. In the 1950s, these governments began to adopt IT for a variety of purposes and functions, and they continue to do so today. Since at least the mid 1970s, a small, but prolific group of scholars has conducted a large body of research on various aspects of IT and local government.2 It is from that research and my own studies into this subject that I have based this chapter (regarding e-government, see also, Norris, 2006). Given the constraint of space, this chapter can only highlight aspects of this important topic. Readers who wish to delve more deeply into the subject of information technology and local government may wish to avail themselves of the works found in the bibliography as well as references from other, related works which can be found through those works.
Digital Libraries
Authors: Altman Micah
Published: May 2011

Digital libraries are collections of digital content and services selected by a curator for use by a particular user community. Digital libraries offer direct access to the content of a wide variety of intellectual works, including text, audio, video, and data; and may offer a variety of services supporting search, access, and collaboration. In the last decade digital libraries have rapidly become ubiquitous because they offer convenience, expanded access, and search capabilities not present in traditional libraries. This has greatly altered how library users find and access information, and has put pressure on traditional libraries to take on new roles. However, information professionals have raised compelling concerns regarding the sizeable gaps in the holdings of digital libraries, about the preservation of existing holdings, and about sustainable economic models. This chapter presents an overview of the history, advantages, disadvantages, and design principles relating to digital libraries, and highlights important controversies and trends. For an excellent comprehensive discussion of the use, cost and benefits of digital libraries see Lesk (2005), for further discussion of architectural and design issues see Arms (2000), and see Witten and Bainbridge (2002) for a detailed example of the mechanics of implementing a digital library.
Privacy Issues in Public Web Sites
Authors: Papathanassiou Eleutherios A. , Mamakou Xenia J.
Published: May 2011

The advent of the Internet has altered the way that individuals find information and has changed how they engage with many organizations, like government, health care, and commercial enterprises. The emergence of the World Wide Web has also resulted in a significant increase in the collection and process of individuals’ information electronically, which has lead to consumers concerns about privacy issues. Many researches have reported the customers’ worries for the possible misuse of their personal data during their transactions on the Internet (Earp & Baumer, 2003; Furnell & Karweni, 1999), while investigation has been made in measuring individuals’ concerns about organizational information privacy practices (Smith, Milberg & Burke, 1996). Information privacy, which “concerns an individual’s control over the processing, that is the acquisition, disclosure, and use, of personal information” (Kang, 1998) has been reported as one of the most important “ethical issues of the information age” (Mason, 1986).
Social Capital and the Gendering of Differential IT Use
Authors: Bryant Lia , Principe Iolanda
Published: May 2011

Public information technology, as a term, implicitly suggests universal access by citizens to information through the use of technology. The concepts of social capital and the digital divide intersect in access to public information technology. Social inclusion or exclusion occurs as a consequence of the ways in which societies are stratified according to race, gender, (dis)ability, ethnicity and class. This chapter focuses on one aspect of stratification, gender and theorizes the gendering of differential access and use of information technologies. An understanding of gendered participation relevant to access to public information technology within the policy contexts for electronic government and social inclusion is important to inform public information technology policy, and service planning and delivery that are premised on the notion of universal access.
Bioterrorism Response and IT Strategies
Authors: Bray David A.
Published: May 2011

Most analyses of possible future bioterrorism events predict they may be similar to the anthrax events of 2001. Specifically, a limited population of individuals may experience morbidity or mortality, but the concern, panic, and worry stirred up by the threat will catch the attention of the entire nation. If public health IT is to help with bioterrorism preparedness, it needs to not only address the mitigation of civilian illnesses and deaths, but also help to manage individual and societal fears springing from the real or threatened occurrence of such an event.
Integrity Protection of Mobile Agent Data
Authors: Guan Sheng-Uei
Published: May 2011

One hindrance to the widespread adoption of mobile-agent technology is the lack of security. Security will be the issue that has to be addressed carefully if mobile agents are to be used in the field of electronic commerce. SAFER (secure agent fabrication, evolution and roaming) is a mobile-agent framework that is specially designed for the purpose of electronic commerce (Guan & Hua, 2003; Guan, Zhu, & Maung, 2004; Zhu, Guan, Yang, & Ko, 2000). Security has been a prime concern from the first day of our research (Guan & Yang, 2002; Yang & Guan, 2000). By building strong and efficient security mechanisms, SAFER aims to provide a trustworthy framework for mobile agents to assist users in conducting mobile or electronic-commerce transactions.
Web Services and Service-Oriented Architectures
Authors: Neubauer Bruce J.
Published: May 2011

A review of the development of information systems can help in understanding the potential significance of Web services and service-oriented architecture (SOA) in the public sector. SOA involves the convergent design of information systems and organizational workflows at the level of services. The purpose of this chapter is to suggest a strategy for mapping the design of service-oriented architectures onto the complex patterns of governance including combinations of federalism, regionalism, and the outsourcing of functions from government agencies to nonprofit organizations. This involves the modeling of workflows and the identification of opportunities for the sharing of services among agencies and nonprofits. The structures of government agencies reflect political jurisdictions, legislative committee structures, areas of public policy, and geographical locations. Federalism creates situations in which multiple agencies (often at different levels of government) have similar responsibilities in the same geographic areas. Metropolitan areas are complex mosaics of local governments and special districts. In addition, nonprofit organizations are also involved in strategic alliances with government agencies to provide services to citizens. The coordination of efforts among multiple organizations has been one of the major functions of public administrators acting through formal or informal networks of relationships within and across organizational boundaries. Web services and SOA can be used to help integrate the often costly and fragmented delivery of government services.
The Strategic Determinants of Shared Services
Authors: Joha Anton , Janssen Marijn
Published: May 2011

Stimulated by recent advances in information and communication technology, and in their continuous pursuit for ways to reduce costs while at the same time improving customer orientation, public agencies have started to share services. By unbundling services of multiple public agencies, standardizing these services, and concentrating them in a separate organization, the basic premise of shared services seems to be that services provided by one local department or agency can be provided to others with relatively few efforts, potentially resulting in both cost savings and service quality improvements (Bergeron, 2003). Public agencies share their role as service provider by joint development, operation, control, and governance of services. As such, the sharing of services can be viewed as a particular type of sourcing arrangement. Services remain within public administration, and public agencies control and govern the shared-service arrangement.