In computer vision, alignment of images plays an important role in different day to day life applications by bringing similar points of images into correspondence. Conventionally, images are aligned by using the extracted features of images. However, the extraction of features is difficult, time consuming and not suitable for low quality images. Whereas pixel based alignment methods are applicable to low quality images and do not require extensive image processing applications. However, these methods are computationally exhaustive that makes it difficult to use for real time applications. Therefore, we need a pixel based method for image alignment that can overcome the limitations of computational complexity. In this paper, we have proposed an efficient Radon transform based method to compute the transformation parameters between two images for aligning them. Moreover, the proposed approach is verified on test images of varying classes and results demonstrate that the proposed method can compute the parameters accurately and efficiently as compared to the existing approaches.

One of the fundamental steps in computer vision and image processing applications is the alignment of images before matching. A number of alignment methods based on features points, pixel information and transformation parameters have been proposed in the literature. All these methods either suffer from accurate detection of feature points or are computationally expensive that makes the entire matching process time consuming. The fast matching of images performed without alignment can benefit a number of image matching applications. In this paper, a transformational approach is proposed that identifies whether two images are similar or not without performing an alignment. The matching without alignment reduces the computation time of the entire matching process. The effectiveness of the proposed approach has been demonstrated on UMD logo dataset. The robustness of the proposed approach to additive noise shows that high accuracy can be achieved even when the noise is as high as 20%. Furthermore, the computation time is improved by decreasing the number of projections without affecting the matching accuracy. The experiments demonstrate that the proposed method is not only efficient but also highly accurate as compared to existing approaches.

In a mobile Peer-to-Peer (P2P) environment, where inherent resource constraints (e.g. battery, bandwidth and computing power) exist, the notion of reliability and efficiency especially around communication of messages between peers is a crucial factor. In this paper, we introduce a trustworthy token-passing multi-point relays (TOP) data dissemination scheme for moving objects in wireless ad-hoc networks. The proposed scheme encompasses the trustworthy model and location-based scheduling technique capable of determining the most optimal schedule for the target peers to receive messages based on the location and mobility parameter. The performance of the proposed approach is compared against the existing state of techniques namely pure flooding and Trustworthiness-based Broadcast (TBB) scheme. The experimental evaluation includes a number of metrics, such as transmission cost, computational cost and message deliverability, of which the results showed promising performance of the proposed scheme.

Unlike the existing relational, hierarchical and object-oriented schemes, associative models can analyze data in similar ways to which our brain links information. Such interactions when implemented in voluminous data clouds can assist in searching for overarching relations in complex and highly distributed data sets with speed and accuracy. In this paper, a different perspective of data recognition will be considered. Rather than looking at conventional approaches, such as statistical computations and deterministic learning schemes, this paper will be focusing on distributed processing approach for scalable data recognition and processing through applying an access scheme that will enable fast data retrieval across multiple records and data segments associatively, utilizing a parallel approach. Doing so will yield a new form of databaselike functionality that can scale up or down over the available infrastructure without interruption or degradation, dynamically and automatically. In our proposed model, data records are treated as patterns. As a result, data storage and retrieval is performed using a distributed pattern recognition approach that is implemented through the integration of loosely-coupled computational networks, followed by a divide-and-distribute approach that facilitates distribution of these networks within the cloud dynamically.

One of the most important issues in fingerprint recognition is that the impressions of different fingers may appear very similar to each other (high inter-class similarity) and likewise, different acquisition of the same finger may be dissimilar from each other (high intra-class variation). To compensate for high intra-class variation and inter-class similarity, this paper addresses two challenging issues in partial fingerprint recognition which are alignment and computing the similarity score. Rotational and displacement variation between registered and query fingerprints occur during scanning. As a consequence, fingerprint alignment is essential to correct for the rotational and translation difference between fingerprints prior to matching. By perfectly aligning the fingerprints, the matching could be simplified. Considering the possibility of high intra-class variation and inter-class similarity, how the similarity score of two fingerprints is computed plays an important role in system's match or non-match decision.

In the exclusive-use model of spectrum trading , cognitive radio devices or secondary users can buy spectrum resources from licensed users or primary users for a short or long period of time. Considering such spectrum access, a trading model is introduced where a buyer can select a set of candidate sellers based on their reputation and their offers in fulfilling its requirements, namely, offered signal quality, contract duration, coverage and bandwidth. Similarly, a seller can assess a buyer as a potential trading partner considering the buyer’s reliability, which the seller can derive from the buyer’s reputation and financial profile. In our scheme, seller reputation or buyer reliability can be either obtained from a reputation brokerage service, if one exists, or calculated using our model. Since in a competitive market, the price of a seller depends on that of other sellers, game theory is used to model the competition among multiple sellers. An optimization technique is used by a buyer to select the best seller(s) and optimize purchase to maximize its utility. This may result in buying from multiple sellers of certain amount of bandwidth from each, depending on price and meeting requirements and budget constraints. Stability of the model is analyzed and performance evaluation shows that it benefits sellers and buyers in terms of profit and throughput, respectively.

Mobile authentication is an essential service to ensure the security of engaging parties in a ubiquitous wireless network environment. Several solutions have been proposed mainly based on both centralised and distributed authentication models to allow ubiquitous mobile access authentication; however, limitations still exist in these approaches, namely flexibility, security and performance issues and vulnerabilities. These shortcomings are influenced by the resource limitations of both wireless networks and the mobile devices together with inter-technology and inter-provider challenges. In this paper, the authors reviewed the major techniques in the field of ubiquitous mobile access authentication, which has attracted many researchers in the past decade. After investigating existing mobile authentication models and approaches, the common challenges are summarised to serve as the solution key requirements. The identified key solution requirements allow analysing and evaluating mobile authentication approaches.

In a mobile environment, data broadcast paradigm has been recognised as an effective and scalable mechanism to disseminate frequently requested information to a large number of mobile users. This paper presents the design and implementation of a power preserving mobile broadcast system. The broadcast system is designed to serve transitive queries or queries that access related data items belonging to different tables in the relational databases. The focus of this paper is revolved around the implementation of three specific data broadcast schemes, namely: (i) a filtering technique for mobile device to perform transitive queries and display the desired data from incoming multiple entity types broadcast data items, (ii) the index broadcast scheme to predict the arrival of the desired data so that power utilization can be minimized, and (iii) multiple channel environments to allow mobile device to tune into multiple broadcast channels to receive the desired data. We showcase the efficacy of these data broadcast schemes through the development of the prototype system with a share indices price application.

Biometrics offers higher accuracy for personal recognition as well as provides greater security than traditional methods because of its properties. However, ironically, these properties are also weaknesses because biometric data is permanently linked with an individual and cannot be revoked or cancelled, especially when biometric data is compromised, which can lead to a serious privacy issue. By reviewing current approaches, fully homomorphic encryption (FHE) is considered as a promising solution for this privacy issue because of its ability to perform computations in the encrypted domain. We studied the effectiveness of FHE when it is used in biometric systems. The main contributions of this paper are the implementation of a privacy-preserving iris biometric authentication protocol adapted to lattice-based FHE and a sound security analysis of authentication and privacy. This work is concluded with some factors to be addressed to enhance privacy as well as some considerations to improve the performance of this implementation.

Partial fingerprints are likely to be fragmentary or low quality, which mandates the development of accurate fingerprint verification algorithms. Two fingerprints should be aligned properly, in order to measure the similarity between them. Moreover, the common fingerprint recognition methods (minutiae-based) only use the limited information that is available. This affects the reliability of the output of the fingerprint recognition system, especially when dealing with partial fingerprints. To overcome this drawback, in this research, a region-based fingerprint recognition method is proposed in which the fingerprints are compared in a pixel-wise manner by computing their correlation coefficient. Therefore, all the attributes of the fingerprint contribute in the matching decision. Such a technique is promising to accurately recognise a partial fingerprint as well as a full fingerprint compared to the minutiae-based fingerprint recognition methods which only concentrate on parts of the fingerprint. The proposed method is based on simple but effective metrics that has been defined to compute local similarities which is then combined into a global score and then used to make the match/non-match decision. Extensive experiments over FVC2002 data set has proven the superiority of our method compared to the other well-known techniques reported in literature.

Data broadcast with its scalability feature provides a strong backbone for the digital information delivery. Such a feature is especially significant for mobile users with inherent power limitations in asymmetric communication environments. This paper presents a specific broadcast ordering scheme supported by advanced structure and access mechanism for ad-hoc queries in mobile data broadcast environments. The proposed scheme aims to minimize both query-access and tuning times by specifying a new message and ordering structure. As a proof of concept, we carry out experimentation of the proposed scheme in comparison with the conventional models. The result of the experiments are presented and discussed in the paper.

A participatory mobile sensing system is designed to enable clients to voluntarily collect environmental data using embedded sensors and a mobile device while going about their daily activities. Due to the spatio-temporal nature of the data, and the significant benefits of the data to the general public, it is necessary to employ an efficient and effective query processing model for the mobile clients to access the data that can be visualized via an interactive multimedia interface. This article introduces a unified on-demand and data broadcast model to serve queries in the context of a mobile sensing system. The contributions of this article include the following: (i) it presents a novel data structure and indexing method to support the system; (ii) it provides flexibility for the client to issue query using on-demand or broadcast channel according to the server load and broadcast schedule; (iii) it enables new data access and processing for the mobile client; and (iv) it is designed for a multiple channels/receivers environment in a 4G wireless network. The proposed model uses a holistic query processing approach for the mobile sensing system that offers substantial efficiency and autonomy for mobile clients when retrieving data. The results of the experiments undertaken affirm the effectiveness of its performance.

This paper introduces a novel clustering-based broadcast scheduling technique for mobile nearest-neighbor (NN) query processing in cyber physical systems. An efficient index structure is presented to guide mobile clients to the NN-objects. The proposed broadcast scheduling and indexing is aimed at minimizing query access time and energy consumption of the clients when retrieving NN-objects through wireless channels. We have experimentally studied the proposed scheme and its comparison with the state-of-the-art methods. The results suggest the efficacy of our proposed approach in offering minimum latency and energy consumption, which is critically important especially for resource-constrained wireless environments.

Activity recognition focuses on inferring current user activities by leveraging sensory data available on todayÕs sensor rich environment. Supervised learning has been applied pervasively for activity recognition. Typical activity recognition techniques process sensory data based on point-by-point approaches. In this paper, we propose a novel cluster-based classification for activity recognition Systems, termed StreamAR. The system incorporates incremental and active learning for mining user activities in data streams. The novel approach processes activities as clusters to build a robust classification framework. StreamAR integrates supervised, unsupervised and active learning and applies hybrid similarity measures technique for recognising activities. Extensive experimental results using real activity recognition datasets have evidenced that our new approach shows improved performance over other existing state-of-the-art learning methods.

A key requirement of biometric matching is to identify people with high level of confidence. This confidence level indicates a degree that the biometric system can reliably decide whether a query biometric template belongs to a registered biometric template or not. This paper explores the use of a template transformation and the longest common substring expression to tackle variability during biometric acquisition and increase the level of confidence of iris biometric matching. The transformation provided with a derivative of the registered template will initially convert the query template to a transformed template that can be used to perform an exact match. When the transformation has been performed, the longest common substring between the registered template and the transformed template is obtained. The proposed transformation will cause the intra-class distributions more homogeneous and push the distributions to a large similarity while the proposed longest common substring will push the inter-class distributions to a large dissimilarity thus minimizing the chance of false acceptances and increasing the separation between the intra-class and inter-class distributions. We extensively tested our proposed method using iris images from the commercial Bath dataset and found that the decidability index (d') and Fisher-ratio can be increased to 82.5 and 3401 respectively. Moreover, the success rate of the transformation to produce exact matches is 96.4%.

This paper introduces an approach to detect reference points for fingerprint images from their local ridge orientation maps. This approach classifies detected singular points into several core and delta point pairs. The validation procedure contains two stages in which the first stage is to remove false pairs of core and delta points and the second stage is to do some post processing of these unpaired singular points. Furthermore, this approach could be extended for reference point detection of arch and partial fingerprint images. The experiments of singular point detection part are conducted on FVC 2002 database 1 and 2. The result shows the average correct rate of singular point detection is 94.05% on the above databases.

Fingerprint is one of the most popular biometric methods for personal identification. In this paper, a novel alignment approach is introduced. This method based on the reference point detection and the texture information surrounding the minutiae. Furthermore, a new matching score calculation method is described to verify the proposed alignment method. The experiment result is also provided, the result shows it has the ERR at 2.61%.

An efficient logical topology helps wireless sensor networks (WSNs) minimizing different constraints. For large-scale WSNs, chain oriented logical topologies are shown to be more energy conservative than other logical topologies. Chain construction is the main challenge to create a chain oriented logical topology. In this paper, we propose a chain construction scheme, which creates several chains for the topology using Voronoi tessellation. The main idea of this scheme is to divide the target field into a number of small areas (i.e., Voronoi cells) so that in each cell, a chain is constructed. To construct a chain in a Voronoi cell, we use a protocol, which guarantees the summation of square to the distances would be the lowest. We compare our chain construction algorithm with other similar algorithms. Simulation results show that proposed Voronoi diagram based algorithm saves more energy, lengthens lifetime of the network, and reduces data collection latency.

Flooding is one type of Denial of Service (DoS) attacks, which can cause significant financial damages. This paper presents a new security approach which can be used to protect government critical systems against DoS flooding attacks. This approach uses a new packet filtering mechanism, called Token Filtering Technique. This technique offers high network client scalability and higher performance in packet filtering rate.

Denial of Service (DoS) attacks can cause significant financial damages, and flooding is one kind of DoS attacks. Some formal models have been proposed to evaluate the functionality of DoS filtering techniques, however, there is no formal model that comprehensively evaluates the effectiveness and efficiency of these techniques. This paper proposes a formal model which can be used for evaluating the performance of protocols and solutions for filtering flooding packets. This model has been used in this paper to evaluate the Token Filter Technique (TFT), a packet filtering technique, as an example. The analysis results show that the TFT offers higher network client scalability and higher performance in packet filtering.

Biometric fuzziness occurs due to variations during data acquisitions and degrades the performance of the iris biometric system. Most of the proposed techniques overcome the fuzziness by removing some parts of the biometric image and/or using image processing methods which are usually computationally inefficient. However, we approach the problem from a post-processing perspective and we start our work with the raw binary iris codes. Our approach is based on the concept of commonality between two codes. The common substrings extract significant structural similarities and the misalignment distance accounts for rotational inconsistencies. This research explores how the length of common substrings can be used as a metric of similarity of iris biometric. We tested our metric using commercial Bath dataset and noticed that it achieves an EER of 1.3%, is robust at handling heterogonous biometric, and is more suitable for low FAR-based applications compared to the widely used Hamming Distance.

Singular points of a fingerprint are considered important global features. They are useful for fingerprint classification and matching because they can reduce the search time and space in large fingerprint databases and can also be regarded as reference points for fingerprint matching. In this paper, we implement a Poincaré Index based approach to detect singular points. Though Poincaré index approach can detect all true ground singular points, it also detects a number of spurious singular points. We use two techniques to remove spurious singular points, one of which is segmentation and the other is smoothing the orientation field of a fingerprint image. We propose a rule based approach to further remove spurious singular points. The experimental results show that our approach achieves total error rate of 8.46% on FVC 2002 databases.

Mobile Internet access has significantly increased over the past few years. Roaming into foreign networks becomes necessary in order to access mobile-services. Traditionally, this done based on roaming agreement between the home network and the foreign network to extend trust for mobile users. However, secured mobile authentication is a challenge especially in two-party authentication environment where only the visited user and the foreign network get involved. This paper proposes two-party secure roaming protocols based on direct negotiation with potential foreign networks regarding quality of service, pricing and other billing related features, in order to establish service agreement and get the authorization token. The paper provides better performance to check the revocation status of the mobile user using recency evidence compare to the previously used revocation list. Identity Based Signature is used to stop impersonation attack. The security and performance analysis indicates that our protocol is resistant to well-known attacks, and it ensures efficient roaming.

Abstract Range search is one of the most common queries in the spatial databases and geographic information systems (GIS). Most range search processing depends on the length of the distance that expresses the relative position of the objects of interest in the Euclidean space or road networks. But, in reality, the expected result is normally constrained by other factors (e.g. number of spatial objects, pre‐defined area, and so forth.) rather than the distance alone; hence, range search should be comprehensively discussed in various scenarios. In this paper, we propose two constrained range search approaches based on network Voronoi diagram, namely Region Constrained Range (RCR) and k nearest neighbor Constrained Range (kCR), which make the range search query processing more flexible to satisfy different requirements in a complex environment. The performance of these approaches is analyzed and evaluated to illustrate that both of them can process constrained range search queries very efficiently. Copyright © 2010 John Wiley & Sons, Ltd.

The inherent limitations of mobile devices (MD) increase the gap between security and performance, and this gap increases with the growing heterogeneity of computing environments. As we are moving to the 4G network and Mobile Internet, there will be a need to deliver an intelligence tradeoff between security and performance. The main aim of this paper is to identify challenges in MD research and to propose practical solution to maintain the balance between efficiency and protection to secure mobile communication. We propose a Dynamic Key Size (DKS) architecture which can be integrated into security protocols to provide an efficient and secure mobile communication. Applications are provided with an interface for selectively securing information at different levels of protection. Our architecture makes use of both the information sensitivity and MD capabilities performance levels classifications in making a decision for suitable algorithm key length. As a possible application, we outline the integration of DKS over SSL protocol to demonstrate the flexibility features that improves the protocol security performance.

Authentication is an important component to protect information systems from unauthorised access of malicious sources. Because of resource limitations of mobile devices, it is a challenge to apply current authentication methods in wired networks for wireless networks. It lacks any considerations of security, efficiency, scalability and flexility in wireless networks. In this paper, an authentication model for individual and group users in wireless network is elaborated. It provides a flexible and scalable model to suit different problem requirements of wireless network services. A realisation of the authentication model using dynamic keys and group key management is proposed and analysed to demonstrate the security and efficiency in wireless networks.

This paper proposes a new global index structure and processing for location-dependent queries in mobile broadcast environments. The proposed scheme consists of two essential elements for addressing spatial queries in broadcast databases. These two elements are: (i) determine the client's location in relevant to the spatial model adopted by the broadcast scheme, and (ii) obtain the required object, which corresponds to the location of the client as determined by the model. The global index's concept will enhance the efficiency of the model. We explore the effectiveness of the proposed index scheme in single and multi channel environments. Performance comparisons with the earlier work through simulated-experiments have also been carried out and the results found have been promising.

Using biometrics for authentication or cryptosystems would require tolerance of errors of the order of 40%. Most of the proposed techniques either use the reliable bits of a biometric or good quality biometric which does not have such a large variation. However, biometric authentication can be viewed as a design of error correcting codes wherein the redundancy provides the tolerance to errors. This paper explores addition of redundancy to support variations as high as 40% in biometrics. We investigated the error characteristics of biometric templates and found that some blocks within the template tend to produce errors higher than the mean error. To handle this behavior we propose a two level correction. We extensively tested our proposed method using iris images from the commercial Bath dataset [13] and found that the proposed method can tolerate the errors with a success rate of 99.07%, while not accepting any imposters.

The purpose of fingerprint image enhancement is to improve the clarity and quality of its local features. The quality of fingerprint image determines the accuracy and reliability of minutia extraction which also determines the accuracy of an automatic fingerprint recognition system. In this paper, we propose an adaptive image pre-processing approach that can significantly improve poor quality images according to their noise level based on contrast stretching, power-law transformation and Gabor filter. The original image smoothing is performed initially by Gaussian filter, and then processed by the proposed adaptive algorithm, and finally the resultant image is filtered by Gabor filter to get the improved binarized image. Experimental results indicate that the proposed approach improves the quality of image and reduces the noise significantly as compared to other fingerprint image preprocessing approaches. Furthermore, the result of Goodness Index (GI) shows that our proposed approach improves the performance by 9% as compared to conventional Gabor filter based approach and is also better than other reported results. Especially, the performance of GI is improved by more than 40% in some poor quality images.

The development of mobile devices and mobile databases boost many spatial queries over moving objects, most of existing mobile applications concentrate on processing mobile queries based on distance metric in Cartesian space. In reality, traveling time is another important metric for spatial queries rather than Euclidean distance or network distance. On the other hand, the spatial queries of moving object monitoring is also restricted by frequent updates, as a result, processing spatial queries over moving objects becomes a tough job, especially in road networks. In this paper, we proposes a time constrained range search query and applies this query over a set of objects moving on the road networks to get a continuous result. By experimental studies, we show that our proposed approach can solve time constrained range search queries properly and the approach for moving objects monitoring outperform its competitors.

Most query searches on road networks are either to find objects within a certain range (range search) or to find k nearest neighbors (kNN) on the actual road network map. In this paper, we propose a novel query, that is, path branch point (PBP). PBP can be defined as given a set of candidate interest objects and a pre-defined path starts from S and end at E, find a path which starts from S, via an interest point P and ends at E. This path should overlap with the user's ad hoc (pre-defined) path as much as possible with an acceptable distance increment. This is a novel query which is motivated by users' common requirements because most users have an ad hoc path in their daily travel and can tolerate a longer driving distance to some extent if they can drive on a familiar path. In this proposed approach, an Adjust Score is calculated for each path which is determined by overlapping distance and increased distance cost. Our experiment verifies the applicability of the proposed approach to solve the queries, which involves finding the optimal path branch points.

Flooding is one type of Denial of Service (DoS) attacks which can cause significant financial losses. This paper presents a new security approach which prevents flooding in the government critical systems and focuses in preventing flooding in non-authenticated client area. A new cooperation with local service providers has been suggested to make the prevention of flooding attacks easier. In addition, dynamic key encryption technique is adapted as a part of the proposed approach to enhance its functionality.

The development in mobile devices and wireless technologies opens up unlimited choices of mobile services such as mobile commerce. These advances make access services available and convenient everywhere at any time. Since mobile users usually move, accessing services becomes unavailable especially in some locations that are not covered by their home networks. Therefore, it becomes necessary to roam into foreign networks in order to access such services. However, authenticating visiting users by a foreign network results in some security concerns. This challenge lies in the fact that a foreign network provider does not initially have the authentication credentials of the mobile users. The existing approaches are either roaming agreement-based in exchanging authentication information between the home network and a foreign network or vulnerable to some security attacks. This paper proposes a roaming agreement-less approach based on our ubiquitous mobile access model. This approach consists of two tokens: Passport (identification token) and Visa (authorisation token) to provide a flexible authentication method for foreign network to authenticate mobile users. The security analysis indicates that our proposal is more secure and suitable for ubiquitous mobile communications specially in roaming agreement-less environment.

Energy consumption and lifetime of networks are the two most important constraints for wireless sensor networks (WSNs). Moreover, for perceiving events with respect to time, WSNs need to maintain coverage quality. This paper focuses on coverage problem with a number of sensors selected from deployed sensor nodes, which develop chain oriented communication. To mitigate the constraints of sensor nodes researchers employ a variety of logical topologies, among which chain oriented topology is one of the significant contender. Moreover, choosing only a selected number of sensors, instead of choosing all of them saves more energy and lengthens lifetime of the network. The main criterion to select a sensor node we propose in this paper is the use of shared sensing region of a sensor node with its neighbours. Simulation results show that our protocol saves a large number of sensor nodes while maintaining significant amount of coverage ratio.

In the data mining field, association rules are discovered having domain knowledge specified as a minimum support threshold. The accuracy in setting up this threshold directly influences the number and the quality of association rules discovered. Often, the number of association rules, even though large in number, misses some interesting rules and the rules' quality necessitates further analysis. As a result, decision making using these rules could lead to risky actions. We propose a framework to discover domain knowledge report as coherent rules. Coherent rules are discovered based on the properties of propositional logic, and therefore, requires no background knowledge to generate them. From the coherent rules discovered, association rules can be derived objectively and directly without knowing the level of minimum support threshold required. We provide analysis of the rules compare to those discovered via the a priori.

One of the most frequent queries in spatial and mobile databases is range search, which is originated from the construction of R-tree that limits the spatial database application to Euclidean distance. Nowadays, Geographic Information System (GIS) demands the applications to be practicable for factual distance, normally identified as network distance. Even though some algorithms are engaged in this area, network distance range search is still a time consuming and storage space occupation task. In this paper, we propose a novel approach which is based on Network Voronoi Diagram that is diffusely used in geometrical analysis. We are looking into how to improve the performance of range search query processing using Network Voronoi Diagram.

The popularity of mobile devices such as mobile phones and Personal Digital Assistants (PDAs) are growing at a fast pace. Mobile devices are able to provide email services to support user's mobility. However, as the wireless environment is inherently insecure, a secure system is required for the service. To secure email systems from being attacked, various approaches have been developed. It is reported that existing technologies still cannot overcome various threats and attacks on the use of conventional passphrases. Motivated by this circumstance, the work presented in this research aims to contribute to an enhanced method of securing email services. A bio-passphrase based on a robust biometric key approach is proposed for OpenPGP to protect the private key. It is planned for mobile devices equipped with iris recognition system. The proposed bio-passphrase is extracted from a crypto-biometric system that merges the iris biometric and cryptographic operations. The proposed crypto-biometric system ensures the avoidance of biometric template storage, either in a central database or a smartcard. Moreover, users may have several bio-passphrases or private keys for different applications as the key diversity can be performed easily. We then demonstrate that our approach can improve the security of email system in wireless environment significantly.

Range search query processing has become one of the most important technologies in spatial and mobile databases. Most literature focuses on static range search extended from one point on both Euclidean distance and actual network distance, but there are only a few methods which can properly solve the problem for moving users, such as searching objects of interest on a road within a certain range. Although there are some techniques, which address continuous search, most approaches are absorbed in the KNN (k nearest neighbour) queries which are a different research area. In this paper, we propose two new methods to process continuous range search query in mobile computing. One is constructed using R-tree index based on Euclidean distance, and the other addresses the requirement on actual network distance.

In a wireless environment, data broadcast paradigm has been recognized as an effective and scalable mechanism to disseminate frequently requested information to a large number of clients. This paper presents the development of a multiple entity types wireless broadcast database system. The broadcast system is designed to serve transitive queries or queries that access related data items belonging to different entity types. The broadcast data are retrieved from a central database server. We apply three different data broadcast schemes including: (i), filtering technique for mobile device to perform transitive queries and display the desired data from incoming multiple entity types broadcast data items; (ii), the index broadcasting scheme designed to predict the arrival of the desired data to appropriately execute power conserving mode; (iii), incorporate multiple channel environments to allow mobile device to tune into multiple broadcast channels to receive the desired data. The proposed model uses a share indices price context to demonstrate the effective use of these data broadcast schemes.

Data broadcasting is a scalable mechanism to disseminate information to a large number of mobile clients in a wireless environment. Our paper concerns with developing a data broadcasting system in a mobile environment, which involves data and index dissemination. The broadcasted data is retrieved from a database server. Subsequently, these data may be broadcasted periodically or aperiodically. As wireless environment inherent resource limitations, the use of indexing scheme will provide efficient data retrieval. We use share indices price context to demonstrate our proposed models. The models are developed using wireless ad-hoc network infrastructure.

Broadcast indexing is necessary to be applied in a wireless broadcast environment as such the scheme helps mobile clients to find the desired data instances efficiently. This is particularly important considering the inherent limitations in mobile environment. In this paper, we present a global indexing scheme for location dependent queries. The proposed scheme is designed to serve queries in which the query result is relevant to client's location. Global indexing scheme aims to minimise index access time while having all the advantages of index broadcasting. We develop a simulation model to find out the access time performance of global indexing scheme as compared to non-global indexing scheme. Additionally, we analyse the efficiency of valid scope used in the global index scheme as compared with an existing valid scope. It is found that global index performs substantially better than the existing indexing concept.

Data broadcasting strategy is known as a scalable way to disseminate information to mobile users. However, with a very large set of broadcast items, the query access time of mobile clients raise accordingly, due to high waiting time for mobile clients to find their data of interest. One possible solution is to split the database information into several broadcast channels. In this paper, we introduce taxonomy of index dissemination for multibroadcast channel based on B* tree structure. We consider three indexing schemes namely: (i) nonreplicated indexing scheme (NRI), (ii) partially-replicated indexing scheme (PRI), and (iii) fully-replicated indexing scheme (FRI). Simulation model is developed to find out the access time performance of each scheme.

Our aim in this research is to make sense of scenes in video. We expect this will enable us to identify different scenes sharing the same semantic, even if they do not share any multimedia cues. Our approach is based on emergence, and involves classification and reasoning. We use patterns of cues to synthesize semantic classifications. These classifications need to be consistent with the observed cues, and suggest other elements that might be present. The suggestions might be based on sets of related patterns, ontology, or other knowledge bases. With an idea of what we are looking for, we can re-examine the scenes for multimedia elements, which support our hypothesis, or at least are not inconsistent. We expect that sufficiently detailed semantic descriptions can be generated, by cycling through these steps.

The growing self-organizing map (GSOM) has been presented as an extended version of the self-organizing map (SOM), which has significant advantages for knowledge discovery applications. In this paper, the GSOM algorithm is presented in detail and the effect of a spread factor, which can be used to measure and control the spread of the GSOM, is investigated. The spread factor is independent of the dimensionality of the data and as such can be used as a controlling measure for generating maps with different dimensionality, which can then be compared and analyzed with better accuracy. The spread factor is also presented as a method of achieving hierarchical clustering of a data set with the GSOM. Such hierarchical clustering allows the data analyst to identify significant and interesting clusters at a higher level of the hierarchy, and as such continue with finer clustering of only the interesting clusters. Therefore, only a small map is created in the beginning with a low spread factor, which can be generated for even a very large data set. Further analysis is conducted on selected sections of the data and as such of smaller volume. Therefore, this method facilitates the analysis of even very large data sets.

Bayesian belief networks have been used widely to solve many decision problem that involve uncertainty. One major advantage of this approach compared with other reasoning tools is its semantic richness in describing the decision process. Some inference algorithms for carrying out the reasoning process exist, but they are known to be computationally expensive. Hence, they require optimisation to make them practical. This paper proposes two optimisation techniques for Bayesian belief networks. These optimisation techniques were investigated for information retrieval applications, but can also be applied to different applications outside the information retrieval area.

The present advances in parallel and distributed processing and its application to database operations such as join resulted in investigating parallel algorithms. Hash based join algorithms involve a costly data partitioning phase prior to the join operation. This paper presents new parallel join algorithms for relations based on grid files where no costly partitioning phase is involved, hence the performance can improve.

Rapidly expanding cellular communication technology, wireless LANs and satellite services have made it possible for mobile users to access information anywhere and at any time. In a mobile computing environment replication might be considered as an essential technique providing reliability, throughput increase and data availability. This paper addresses the replica control protocols with an emphasis on workstation mobility issues. The modifications that have to be made to the primary copy method for replicated database management strategies in order to address the effect of mobility on the existing replica control protocols are analysed and proposed. A variation of the primary copy algorithm, called virtual primary copy method is proposed and it is shown that this method is well suited for the distributed mobile computing environment. The performance of virtual primary copy method comparative to traditional primary copy method using computer simulation is analysed.