Selection of intrusion detection system threshold bounds for effective sensor fusion

The motivation behind the fusion of Intrusion Detection Systems was the realization that with the increasing traffic and increasing complexity of attacks, none of the present day stand-alone Intrusion Detection Systems can meet the high demand for a very high detection rate and an extremely low false positive rate. Multi-sensor fusion can be used to meet these requirements by a refinement of the combined response of different Intrusion Detection Systems. In this paper, we show the design technique of sensor fusion to best utilize the useful response from multiple sensors by an appropriate adjustment of the fusion threshold. The threshold is generally chosen according to the past experiences or by an expert system. In this paper, we show that the choice of the threshold bounds according to the Chebyshev inequality principle performs better. This approach also helps to solve the problem of scalability and has the advantage of failsafe capability. This paper theoretically models the fusion of Intrusion Detection Systems for the purpose of proving the improvement in performance, supplemented with the empirical evaluation. The combination of complementary sensors is shown to detect more attacks than the individual components. Since the individual sensors chosen detect sufficiently different attacks, their result can be merged for improved performance. The combination is done in different ways like (i) taking all the alarms from each system and avoiding duplications, (ii) taking alarms from each system by fixing threshold bounds, and (iii) rule-based fusion with a priori knowledge of the individual sensor performance. A number of evaluation metrics are used, and the results indicate that there is an overall enhancement in the performance of the combined detector using sensor fusion incorporating the threshold bounds and significantly better performance using simple rule-based fusion.

Computing complete test graphs for hierarchical systems

Conformance testing focuses on checking whether an implementation. under test (IUT) behaves according to its specification. Typically, testers are interested it? performing targeted tests that exercise certain features of the IUT This intention is formalized as a test purpose. The tester needs a "strategy" to reach the goal specified by the test purpose. Also, for a particular test case, the strategy should tell the tester whether the IUT has passed, failed. or deviated front the test purpose. In [8] Jeron and Morel show how to compute, for a given finite state machine specification and a test purpose automaton, a complete test graph (CTG) which represents all test strategies. In this paper; we consider the case when the specification is a hierarchical state machine and show how to compute a hierarchical CTG which preserves the hierarchical structure of the specification. We also propose an algorithm for an online test oracle which avoids a space overhead associated with the CTG.

Scalable non-linear Support Vector Machine using hierarchical clustering

This paper discusses a method for scaling SVM with Gaussian kernel function to handle large data sets by using a selective sampling strategy for the training set. It employs a scalable hierarchical clustering algorithm to construct cluster indexing structures of the training data in the kernel induced feature space. These are then used for selective sampling of the training data for SVM to impart scalability to the training process. Empirical studies made on real world data sets show that the proposed strategy performs well on large data sets.

Expression of drug resistance markers by spheroplasts ofMycobacterium smegmatis after fusion

Mycobacterial spheroplasts were prepared by treatment of the glycinesensitized cells with a combination of lipase and lysozyme. They were stable for several hours at room temperature but were lysed on treatment with 0.1% sodium dodecyl sulfate. The spheroplasts could be regenerated on a suitable medium. Fusion and regeneration of the spheroplasts were attempted using drug resistant mutant strains ofM. smegmalis. Recombinants were obtained from spheroplast fusion mediated by polyethylene glycol and dimethyl sulfoxide. Simultaneous expression of rccombinant properties was observed only after an initial lag in the isolated clones. This has been explained as due to “chromosome inactivation” in the fused product.

Functional nanoporous structures by partial sintering of nanorod assemblies

We present a general method for the synthesis of functional nanoporous structures by heat treating a loose compact of nanorods. Partial sintering of such a compact leads to spherodization of the nanorods and their fusion at the contact regions leading to an interconnected porous microstructure. The pore diameter can be controlled by changing the original nanorod diameter. We illustrate the generality of the method using TiO2, ZnO and hydroxyapatite as model systems; the method is applicable for any material that can be grown in the form of nanorods. The kinetics of the sintering process can be significantly enhanced in systems in which additional driving forces for mass transport arise from phase transitions proving an ultrafast pathway for producing biphasic porous structures. The possibility of producing hierarchical porous structures using fugitive sintering aids makes this process ideal for a variety of applications including catalysis, photoanodes for solar cells and scaffolds for biomedical applications.

Fusion of Complementary Online and Offline Strategies for Recognition of Handwritten Kannada Characters

This work describes an online handwritten character recognition system working in combination with an offline recognition system. The online input data is also converted into an offline image, and parallely recognized by both online and offline strategies. Features are proposed for offline recognition and a disambiguation step is employed in the offline system for the samples for which the confidence level of the classifier is low. The outputs are then combined probabilistically resulting in a classifier out-performing both individual systems. Experiments are performed for Kannada, a South Indian Language, over a database of 295 classes. The accuracy of the online recognizer improves by 11% when the combination with offline system is used.

Choice of Classifiers in Hierarchical Recognition of Online Handwritten Kannada and Tamil Aksharas

In this paper, we propose a novel dexterous technique for fast and accurate recognition of online handwritten Kannada and Tamil characters. Based on the primary classifier output and prior knowledge, the best classifier is chosen from set of three classifiers for second stage classification. Prior knowledge is obtained through analysis of the confusion matrix of primary classifier which helped in identifying the multiple sets of confused characters. Further, studies were carried out to check the performance of secondary classifiers in disambiguating among the confusion sets. Using this technique we have achieved an average accuracy of 92.6% for Kannada characters on the MILE lab dataset and 90.2% for Tamil characters on the HP Labs dataset.

Hierarchical Directory-Based Shared Memory Architecture

We describe the design of a directory-based shared memory architecture on a hierarchical network of hypercubes. The distributed directory scheme comprises two separate hierarchical networks for handling cache requests and transfers. Further, the scheme assumes a single address space and each processing element views the entire network as contiguous memory space. The size of individual directories stored at each node of the network remains constant throughout the network. Although the size of the directory increases with the network size, the architecture is scalable. The results of the analytical studies demonstrate superior performance characteristics of our scheme compared with those of other schemes.

Estimating the Threshold Surface Density of Gp120-CCR5 Complexes Necessary for HIV-1 Envelope-Mediated Cell-Cell Fusion

Reduced expression of CCR5 on target CD4(+) cells lowers their susceptibility to infection by R5-tropic HIV-1, potentially preventing transmission of infection and delaying disease progression. Binding of the HIV-1 envelope (Env) protein gp120 with CCR5 is essential for the entry of R5 viruses into target cells. The threshold surface density of gp120-CCR5 complexes that enables HIV-1 entry remains poorly estimated. We constructed a mathematical model that mimics Env-mediated cell-cell fusion assays, where target CD4(+)CCR5(+) cells are exposed to effector cells expressing Env in the presence of a coreceptor antagonist and the fraction of target cells fused with effector cells is measured. Our model employs a reaction network-based approach to describe protein interactions that precede viral entry coupled with the ternary complex model to quantify the allosteric interactions of the coreceptor antagonist and predicts the fraction of target cells fused. By fitting model predictions to published data of cell-cell fusion in the presence of the CCR5 antagonist vicriviroc, we estimated the threshold surface density of gp120-CCR5 complexes for cell-cell fusion as similar to 20 mu m(-2). Model predictions with this threshold captured data from independent cell-cell fusion assays in the presence of vicriviroc and rapamycin, a drug that modulates CCR5 expression, as well as assays in the presence of maraviroc, another CCR5 antagonist, using sixteen different Env clones derived from transmitted or early founder viruses. Our estimate of the threshold surface density of gp120-CCR5 complexes necessary for HIV-1 entry thus appears robust and may have implications for optimizing treatment with coreceptor antagonists, understanding the non-pathogenic infection of non-human primates, and designing vaccines that suppress the availability of target CD4(+)CCR5(+) cells.

Synthesis and vesicle formation from dimeric pseudoglyceryl lipids with (CH2)(m) spacers: pronounced m-value dependence of thermal properties, vesicle fusion, and cholesterol complexation

Eight new dimeric lipids, in which the two Me2N+ ion headgroups are separated by a variable number of polymethylene units [-(CH2)(m)-], have been synthesized. The electron micrograph (TEM) and dynamic light scattering (DLS) of their aqueous dispersions confirmed the formation of vesicular-type aggregates. The vesicle sizes and morphologies were found to depend strongly on the m value, the method, and thermal history of the vesicle preparation. Information on the thermotropic properties of the resulting vesicles was obtained from microcalorimetry and temperature-dependent fluorescence anisotropy measurements. Interestingly, the T-m values for these vesicles revealed a nonlinear dependence on spacer chain length (m value). These vesicles were able to entrap riboflavin. The rates of permeation of the OH- ion under an imposed transmembrane pH gradient were also found to depend significantly on the m value. X-Ray diffraction of the cast films of the lipid dispersions elucidated the nature and the thickness of these membrane organizations, and it was revealed that these lipids organize in three different ways depending on the m value. The EPR spin-probe method with the doxylstearic acids 5NS, 12NS, and 16NS, spin-labeled at various positions of stearic acid, was used to establish, the chain-flexibility gradient and homogeneity of these bilayer assemblies. The apparent fusogenic propensities of these bipolar tetraether lipids were investigated in the presence of Na2SO4 with fluorescence-resonance energy-transfer fusion assay. Small unilamellar vesicles formed from 1 and three representative biscationic lipids were also studied with fluorescence anisotropy and H-1 NMR spectroscopic techniques in the absence and the presence of varying amounts of cholesterol.

Characterization of the gene encoding the envelope fusion glycoprotein GP64 from Bombyx mori nucleopolyhedrovirus

We describe here the characterization of the gene gp64 encoding the envelope fusion protein GP64 (open reading frame) ORF 105 from Bombyx mori nucleopolyhedrovirus (BmNPV). gp64 was transcribed from the early to late stages of infection and the transcripts were seen from 6 to 72 h post infection (hpi). The early transcripts initiated from a consensus CAGT motif while the late transcripts arose from three conserved TAAG motifs, all of which were located in the near upstream region of the coding sequence. Both early and late transcripts terminated at a run of T residues following the second polyadenylation signal located 31 nt downstream of the translation termination codon. BmGP64 protein was detectable from 6 hpi and was present in larger quantities throughout the infection process from 12 hpi, in BmNPV-infected BmN cells. The persistent presence of GP64 in BmN cells differed from the protein expression pattern of GP64 in Autographa californica multinucleocapsid nucleopolyhedrovirus infection, where the protein levels decreased significantly by late times (48 hpi). BmGP64 was located in the membrane and cytoplasm of the infected host cells and as a component of the budded virions. The production of infectious budded virus and the fusion activity were reduced when glycosylation of GP64 was inhibited. (C) 2003 Elsevier Science B.V. All rights reserved.

Image fusion in GRDSS for Land use Mapping

Image fusion techniques are useful to integrate the geometric detail of a high-resolution panchromatic (PAN) image and the spectral information of a low-resolution multispectral (MSS) image, particularly important for understanding land use dynamics at larger scale (1:25000 or lower), which is required by the decision makers to adopt holistic approaches for regional planning. Fused images can extract features from source images and provide more information than one scene of MSS image. High spectral resolution aids in identification of objects more distinctly while high spatial resolution allows locating the objects more clearly. The geoinformatics technologies with an ability to provide high-spatial-spectral-resolution data helps in inventorying, mapping, monitoring and sustainable management of natural resources. Fusion module in GRDSS, taking into consideration the limitations in spatial resolution of MSS data and spectral resolution of PAN data, provide high-spatial-spectral-resolution remote sensing images required for land use mapping on regional scale. GRDSS is a freeware GIS Graphic User Interface (GUI) developed in Tcl/Tk is based on command line arguments of GRASS (Geographic Resources Analysis Support System) with the functionalities for raster analysis, vector analysis, site analysis, image processing, modeling and graphics visualization. It has the capabilities to capture, store, process, analyse, prioritize and display spatial and temporal data.

Mathematical Analysis of Sensor Fusion for Intrusion Detection Systems

Fusion of multiple intrusion detection systems results in a more reliable and accurate detection for a wider class of intrusions. The paper presented here introduces the mathematical basis for sensor fusion and provides enough support for the acceptability of sensor fusion in performance enhancement of intrusion detection systems. The sensor fusion system is characterized and modeled with no knowledge of the intrusion detection systems and the intrusion detection data. The theoretical analysis is supported with an experimental illustration with three of the available intrusion detection systems using the DARPA 1999 evaluation data set.