String matching query verification on the cloud-hosted databases

Database query verification schemes attempt to provide authenticity, completeness, and freshness guarantees for queries executed on untrusted cloud servers. A number of such schemes currently exist in the literature, allowing query verification for queries that are based on matching whole values (such as numbers, dates, etc.) or for queries based on keyword matching. However, there is a notable gap in the research with regard to query verification schemes for pattern-matching queries. Our contribution here is to provide such a verification scheme that provides correctness guarantees for pattern-matching queries executed on the cloud. We describe a trivial scheme, ȃŸż and show how it does not provide completeness guarantees, and then proceed to describe our scheme based on efficient primitives such as cryptographic hashing and Merkle hash trees along with suffix arrays. We also provide experimental results based on a working prototype to show the practicality of our scheme.Ÿż

Classifying DDoS packets in high-speed networks

Recently high-speed networks have been utilized by attackers as Distributed Denial of Service (DDoS) attack infrastructure. Services on high-speed networks also have been attacked by successive waves of the DDoS attacks. How to sensitively and accurately detect the attack traffic, and quickly filter out the attack packets are still the major challenges in DDoS defense. Unfortunately most current defense approaches can not efficiently fulfill these tasks. Our approach is to find the network anomalies by using neural network and classify DDoS packets by a Bloom filter-based classifier (BFC). BFC is a set of spaceefficient data structures and algorithms for packet classification. The evaluation results show that the simple complexity, high classification speed and accuracy and low storage requirements of this classifier make it not only suitable for DDoS filtering in high-speed networks, but also suitable for other applications such as string matching for intrusion detection systems and IP lookup for programmable routers.

Extracting common subtrees from decision trees

This paper explores an efficient technique for the extraction of common subtrees in decision trees. The method is based on a Suffix Tree string matching process and the algorithm is applied to the problem of finding common decision rules in path planning.

Two-dimensional string notation for representing video sequences

Most current work on video indexing concentrates on queries which operate over high level semantic information which must be entirely composed and entered manually. We propose an indexing system which is based on spatial information about key objects in a scene. These key objects may be detected automatically, with manual supervision, and tracked through a sequence using one of a number of recently developed techniques. This representation is highly compact and allows rapid resolution of queries specified by iconic example. A number of systems have been produced which use 2D string notations to index digital image libraries. Just as 2D strings provide a compact and tractable indexing notation for digital pictures, a sequence of 2D strings might provide an index for a video or image sequence. To improve further upon this we reduce the representation to the 2D string pair representing the initial frame, and a sequence of edits to these strings. This takes advantage of the continuity between frames to further reduce the size of the notation. By representing video sequences using string edits, a notation has been developed which is compact, and allows querying on the spatial relationships of objects to be performed without rebuilding the majority of the scene. Calculating ranks of objects directly from the edit sequence allows matching with minimal calculation, thus greatly reducing search time. This paper presents the edit sequence notation and algorithms for evaluating queries over image sequences. A number of optimizations which represent a considerably saving in search time is demonstrated in the paper.

Google hacking defence based on honey pages

 Many web servers contain some dangerous pages (we name them eigenpages) that can indicate their vulnerabilities. Therefore, some worms such as Santy locate their targets by searching for these eigenpages in search engines with well-crafted queries. In this paper, we focus on the modeling and containment of these special worms targeting web applications. We propose a containment system based on honey pots. We make search engines randomly insert a few honey pages that will induce visitors to the pre-established honey pots among the search results for the arriving queries. And then infectious can be detected and reported to the search engines when their malicious scans hit the honey pots. We find that the Santy worm can be well stopped by inserting no more than two honey pages in every one hundred search results. We also solve the challenging issue to dynamically generate matching honey pages for those dynamically arriving queries. Finally, a prototype is implemented to prove the technical feasibility of this system. © 2013 by CESER Publications.

Neglect dyslexia with a stimulus-centred deficit and without visuospatial neglect.

This paper reports a single case of ipsilesional left neglect dyslexia and interprets it according to the three-level model of visual word recognition proposed by Caramazza and Hillis (1990). The three levels reflect a progression from the physical stimulus to an abstract representation of a word. RR was not impaired at the first, retinocentric, level, which represents the individual features of letters within a word according to the location of the word in the visual field: She made the same number of errors to words presented in her left visual field as in her right visual field. A deficit at this level should also mean the patient neglects all stimuli. This did not occur with RR: She did not neglect when naming the items in rows of objects and rows of geometric symbols. In addition, although she displayed significant neglect dyslexia when making visual matching judgements on pairs of words and nonwords, she did not do so to pairs of nonsense letter shapes, shapes which display the same level of visual complexity as letters in words. RR was not impaired at the third, graphemic, level, which represents the ordinal positions of letters within a word: She continued to neglect the leftmost (spatial) letter of words presented in mirror-reversed orientation and she did not neglect in oral spelling. By elimination, these results suggest RR's deficit affects a spatial reference frame where the representational space is bounded by the stimulus: A stimulus-centred level of representation. We define five characteristics of a stimulus-centred deficit, as manifest in RR. First, it is not the case that neglect dyslexia occurs because the remaining letters in a string attract or capture attention away from the leftmost letter(s). Second, the deficit is continuous across the letter string. Third, perceptually significant features, such as spaces, define potential words. Fourth, the whole, rather than part, of a letter is neglected. Fifth, category information is preserved. It is concluded that the Caramazza-Hillis model accounts well for RR's data, although we conclude that neglect dyslexia can be present when a more general visuospatial neglect is absent.

Algorithm for web services matching

UDDI is a standard for publishing and discovery of web services. UDDI registries provide keyword searches for web services. The search functionality is very simple and fails to account for relationships between web services. In this paper, we propose an algorithm which retrieves closely related web services. The proposed algorithm is based on singular value decomposition (SVD) in linear algebra, which reveals semantic relationships among web services. The preliminary evaluation shows the effectiveness and feasibility of the algorithm.

Giving content to the principle of proportionality: happiness and pain as the universal currency for matching offence seriousness and penalty severity

The principle of proportionality prescribes that the punishment should equal the crime. It is one of the most important principles of sentencing. Yet, despite its widespread acceptance it offers no meaningful guide to sentencing. Hence penalty levels fluctuate greatly between jurisdictions and within jurisdictions. This is because there is no universally agreed criterion for measuring offence seriousness or penalty severity. This article suggests that the appropriate criteria for matching offence seriousness and penalty severity is the level of unhappiness or pain stemming from each of these impositions. Thus, for example, the level of pain meted out to a rape offender should equal the level of pain caused to a rape victim. Emerging scientific studies on human well-being and happiness show that human beings are similarly built in terms of the experiences that are either conducive or inimical to well-being. This commonality provides a strong foundation to be confident to make reasonably accurate predictions concerning the extent to which adverse events, such as being the victim of a criminal offence or subjected to a form of criminal sanction will stifle human flourishing. This will then allow us to match accurately offence seriousness and penalty level.

MDSM: microarray database schema matching using the Hungarian method

Current microarray databases use different terminologies and structures and thereby limit the sharing of data and collating of results between laboratories. Consequently, an effective integrated microarray data model is required. One important process to develop such an integrated database is schema matching. In this paper, we propose an effective schema matching approach called MDSM, to syntactically and semantically map attributes of different microarray schemas. The contribution from this work will be used later to create microarray global schemas. Since microarray data is complex, we use microarray ontology to improve the measuring accuracy of the similarity between attributes. The similarity relations can be represented as weighted bipartite graphs. We determine the best schema matching by computing the optimal matching in a bipartite graph using the Hungarian optimisation method. Experimental results show that our schema matching approach is effective and flexible to use in different kinds of database models such as; database schema, XML schema, and web site map. Finally, a case study on an existing public microarray schema is carried out using the proposed method.

Image matching using TI multi-wavelet transform

A multi-resolution image matching technique based on multiwavelets followed by a coarse to fine strategy is presented. The technique addresses the estimation of optimal corresponding points and the corresponding disparity maps in the presence of occlusion, ambiguity and illuminative variations in the two perspective views taken by two different cameras or at different lighting conditions. The problem of occlusion and ambiguity is addressed by a geometric topological refining approach along with the uniqueness constraint whereas the illuminative variation is dealt by using windowed normalized correlation.

Fingerprint recognition system using hybrid matching techniques

With an increasing emphasis on the emerging automatic person identification application, biometrics based, especially fingerprint-based identification, is receiving a lot of attention. This research developed an automatic fingerprint recognition system (AFRS) based on a hybrid between minutiae and correlation based techniques to represent and to match fingerprint; it improved each technique individually. It was noticed that, in the hybrid approach, as a result of an improvement of minutiae extraction algorithm in post-process phase that combines the two algorithms, the performance of the minutia algorithm improved. An improvement in the ridge algorithm that used centre point in fingerprint instead of reference point was also observed. Experiments indicate that the hybrid technique performs much better than each algorithm individually.