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.

The effects of manganese content and mould size on abrasion and slurry erosion behaviour of chromium-manganese iron systems investigated by positron lifetime spectroscopy

Abrasion and slurry erosion behaviour of chromium-manganese iron samples with chromium (Cr) in the range similar to 16-19% and manganese (Mn) at 5 and 10% levels have been characterized for hardness followed by microstructural examination using optical and scanning electron microscopy. Positron lifetime studies have been conducted to understand the defects/microporosity influence on the microstructure. The samples were heat treated and characterized to understand the structural transformations in the matrix. The data reveals that hardness decreased with increase in Mn content from 5 to 10% in the first instance and then increase in the section size in the other case, irrespective of the sample conditions. The abrasion and slurry erosion losses show increase with increase in the section size as well as with increase in Mn content. The positron results show that as hardness increases from as-cast to heat treated sample, the positron trapping rate and hence defect concentration showed opposite trend as expected. So a good correlation between defects concentration and the hardness has been observed. These findings also corroborate well with the microstructural features obtained from optical and scanning electron microscopy. (C) 2009 Elsevier B. V. All rights reserved.

Studies of Adsorption Characteristics of Activated Carbons Down to 4.5 K for the Development of Cryosorption Pumps for Fusion Systems

Cryosorption pump is the only possible device to pump helium, hydrogen and its isotopes in fusion environment, such as high magnetic field and high plasma temperatures. Activated carbons are known to be the most suitable adsorbent in the development of cryosorption pumps. For this purpose, the data of adsorption characteristics of activated carbons in the temperature range 4.5 K to 77 K are needed, but are not available in the literature. For obtaining the above data, a commercial micro pore analyzer operating at 77 K has been integrated with a two stage GM cryocooler, which enables the cooling of the sample temperature down to 4.5 K. A heat switch mounted between the second stage cold head and the sample chamber helps to raise the sample chamber temperature to 77 K without affecting the performance of the cryocooler. The detailed description of this system is presented elsewhere. This paper presents the results of experimental studies of adsorption isotherms measured on different types of activated carbons in the form of granules, globules, flake knitted and non-woven types in the temperature range 4.5 K to 10 K using Helium gas as the adsorbate. The above results are analyzed to obtain the pore size distributions and surface areas of the activated carbons. The effect of adhesive used for bonding the activated carbons to the panels is also studied. These results will be useful to arrive at the right choice of activated carbon to be used for the development of cryosorption pumps.

Speaker verification based on the fusion of speech acoustics and inverted articulatory signals

We propose apractical, feature-level and score-level fusion approach by combining acoustic and estimated articulatory information for both text independent and text dependent speaker verification. From a practical point of view, we study how to improve speaker verification performance by combining dynamic articulatory information with the conventional acoustic features. On text independent speaker verification, we find that concatenating articulatory features obtained from measured speech production data with conventional Mel-frequency cepstral coefficients (MFCCs) improves the performance dramatically. However, since directly measuring articulatory data is not feasible in many real world applications, we also experiment with estimated articulatory features obtained through acoustic-to-articulatory inversion. We explore both feature level and score level fusion methods and find that the overall system performance is significantly enhanced even with estimated articulatory features. Such a performance boost could be due to the inter-speaker variation information embedded in the estimated articulatory features. Since the dynamics of articulation contain important information, we included inverted articulatory trajectories in text dependent speaker verification. We demonstrate that the articulatory constraints introduced by inverted articulatory features help to reject wrong password trials and improve the performance after score level fusion. We evaluate the proposed methods on the X-ray Microbeam database and the RSR 2015 database, respectively, for the aforementioned two tasks. Experimental results show that we achieve more than 15% relative equal error rate reduction for both speaker verification tasks. (C) 2015 Elsevier Ltd. All rights reserved.

Translational fusion of two beta-subunits of human chorionic gonadotropin results in production of a novel antagonist of

The strategy of translationally fusing the alpha-and beta-subunits of human chorionic gonadotropin (hCG) into a single-chain molecule has been used to produce novel analogs of hCG. Previously we reported expression of a biologically active singlechain analog hCG alpha beta expressed using Pichia expression system. Using the same expression system, another analog, in which the alpha-subunit was replaced with the second beta-subunit, was expressed (hCG beta beta) and purified. hCG beta beta could bind to LH receptor with an affinity three times lower than that of hCG but failed to elicit any response. However, it could inhibit response to the hormone in vitro in a dose- dependent manner. Furthermore, it inhibited response to hCG in vivo indicating the antagonistic nature of the analog. However, it was unable inhibit human FSH binding or response to human FSH, indicating the specificity of the effect. Characterization of hCG alpha beta and hCG beta beta using immunological tools showed alterations in the conformation of some of the epitopes, whereas others were unaltered. Unlike hCG, hCG beta beta interacts with two LH receptor molecules. These studies demonstrate that the presence of the second beta-subunit in the single-chain molecule generated a structure that can be recognized by the receptor. However, due to the absence of alpha-subunit, the molecule is unable to elicit response. The strategy of fusing two beta-subunits of glycoprotein hormones can be used to produce antagonists of these hormones.

Experimental and Computational Characterization of Alloy--Spinel--Corundum Equilibrium in the System Fe--Co--Al--O at 1873K

The three-phase equilibrium between alloy, spinel solid solution and alpha -Al sub 2 O sub 3 in the Fe--Co--Al--O system at 1873k was fully characterized as a function of alloy composition using both experimental and computational methods. The equilibrium oxygen content of the liquid alloy was measured by suction sampling and inert gas fusion analysis. The O potential corresponding to the three-phase equilibrium was determined by emf measurements on a solid state galvanic cell incorporating (Y sub 2 O sub 3 )ThO sub 2 as the solid electrolyte and Cr + Cr sub 2 O sub 3 as the reference electrode. The equilibrium composition of the spinel phase formed at the interface between the alloy and alumina crucible was measured by electron probe microanalysis (EPMA). The experimental results were compared with the values computed using a thermodynamic model. The model used values for standard Gibbs energies of formation of pure end-member spinels and Gibbs energies of solution of gaseous O in liquid Fe and cobalt available in the literature. The activity--composition relationship in the spinel solid solution was computed using a cation distribution model. The variation of the activity coefficient of O with alloy composition in the Fe--Co--O system was estimated using both the quasichemical model of Jacob and Alcock and Wagner's model along with the correlations of Chiang and Chang and Kuo and Chang. The computed results of spinel composition and O potential are in excellent agreement with the experimental data. Graphs. 29 ref.--AA

CUSUM Based Distributed Detection in WSNs

We are concerned with the situation in which a wireless sensor network is deployed in a region, for the purpose of detecting an event occurring at a random time and at a random location. The sensor nodes periodically sample their environment (e.g., for acoustic energy),process the observations (in our case, using a CUSUM-based algorithm) and send a local decision (which is binary in nature) to the fusion centre. The fusion centre collects these local decisions and uses a fusion rule to process the sensors’ local decisions and infer the state of nature, i.e., if an event has occurred or not. Our main contribution is in analyzing two local detection rules in combination with a simple fusion rule. The local detection algorithms are based on the nonparametric CUSUMprocedure from sequential statistics. We also propose two ways to operate the local detectors after an alarm. These alternatives when combined in various ways yield several approaches. Our contribution is to provide analytical techniques to calculate false alarm measures, by the use of which the local detector thresholds can be set. Simulation results are provided to evaluate the accuracy of our analysis. As an illustration we provide a design example. We also use simulations to compare the detection delays incurred in these algorithms.

Pixel based fusion using IKONOS imagery

Pixel based image fusion entails combining geometric details of a high-resolution Panchromatic (PAN) image and spectral information of a low-resolution Multispectral (MS) image to produce images with highest spatial content while preserving the spectral information. This work reviews and implements six fusion techniques – À Trous algorithm based wavelet transform (ATW), Mulitresolution Analysis based Intensity Modulation, Gram Schmidt fusion, CN Spectral, Luminance Chrominance and High pass fusion (HPF) on IKONOS imagery having 1 m PAN and 4 m MS channels. Comparative performance analysis of techniques by various methods reveals that ATW followed by HPF perform best among all the techniques.

Measurement and modeling of Alloy-Spinel-Corundum equilibrium in the Ni-Mn-Al-0 system at 1873 K

The oxygen content of liquid Ni-Mn alloy equilibrated with spinel solid solution, (Ni,Mn)O. (1 +x)A12O3, and α-Al2O3 has been measured by suction sampling and inert gas fusion analysis. The corresponding oxygen potential of the three-phase system has been determined with a solid state cell incorporating (Y2O3)ThO2 as the solid electrolyte and Cr + Cr2O3 as the reference electrode. The equilibrium composition of the spinel phase formed at the interface of the alloy and alumina crucible was obtained using EPMA. The experimental data are compared with a thermodynamic model based on the free energies of formation of end-member spinels, free energy of solution of oxygen in liquid nickel, interaction parameters, and the activities in liquid Ni-Mn alloy and spinel solid solution. Mixing properties of the spinel solid solution are derived from a cation distribution model. The computational results agree with the experimental data on oxygen concentration, potential, and composition of the spinel phase.

Effect of signal peptide on stability and folding of escherichia coli thioredoxin

The signal peptide plays a key role in targeting and membrane insertion of secretory and membrane proteins in both prokaryotes and eukaryotes. In E. coli, recombinant proteins can be targeted to the periplasmic space by fusing naturally occurring signal sequences to their N-terminus. The model protein thioredoxin was fused at its N-terminus with malE and pelB signal sequences. While WT and the pelB fusion are soluble when expressed, the malE fusion was targeted to inclusion bodies and was refolded in vitro to yield a monomeric product with identical secondary structure to WT thioredoxin. The purified recombinant proteins were studied with respect to their thermodynamic stability, aggregation propensity and activity, and compared with wild type thioredoxin, without a signal sequence. The presence of signal sequences leads to thermodynamic destabilization, reduces the activity and increases the aggregation propensity, with malE having much larger effects than pelB. These studies show that besides acting as address labels, signal sequences can modulate protein stability and aggregation in a sequence dependent manner.

Ozone and carbon trioxide synthesis by low energy ion implantation onto solid carbon dioxide and implications to astrochemistry

Ion implantation experiments were carried out on amorphous (30 K) and crystalline (80 K) solid CO2 using both reactive (D+, H+) and non-reactive (He+) ions, simulating different irradiation environments on satellite and dust grain surfaces. Such ion irradiation synthesized several new species in the ice including ozone (O-3), carbon trioxide (CO3), and carbon monoxide (CO) the main dissociation product of carbon dioxide. The yield of these products was found to be strongly dependent upon the ion used for irradiation and the sample temperature. Ion implantation changes the chemical composition of the ice with recorded infrared spectra clearly showing the coexistence of D-3h and C-2v isomers of CO3, for the first time, in ion irradiated CO2 ice. (C) 2013 AIP Publishing LLC.

A fluorescent molecularly-imprinted polymer gate with temperature and pH as inputs for detection of alpha-fetoprotein

In this work, we have reported a new approach on the use of stimuli-responsive molecularly imprinted polymer (MIP) for trace level sensing of alpha-fetoprotein (AFP), which is a well know cancer biomarker. The stimuli-responsive MIP is composed of three components, a thermo-responsive monomer, a pH responsive component (tyrosine derivative) and a highly fluorescent vinyl silane modified carbon dot. The synthesized AFP-imprinted polymer possesses excellent selectivity towards their template molecule and dual-stimuli responsive behavior. Along with this, the imprinted polymer was also explored as `OR' logic gate with two stimuli (pH and temperature) as inputs. However, the non-imprinted polymers did not have such `OR' gate property, which confirms the role of template binding. The imprinted polymer was also used for estimation of AFP in the concentration range of 3.96-80.0 ng mL(-1), with limit of detection (LOD) 0.42 ng mL(-1). The role of proposed sensor was successfully exploited for analysis of AFP in real human blood plasma, serum and urine sample. (C) 2015 Elsevier B.V. All rights reserved.

A Scalable High Throughput Firewall in FPGA

High end network security applications demand high speed operation and large rule set support. Packet classification is the core functionality that demands high throughput in such applications. This paper proposes a packet classification architecture to meet such high throughput. We have implemented a Firewall with this architecture in reconflgurable hardware. We propose an extension to Distributed Crossproducting of Field Labels (DCFL) technique to achieve scalable and high performance architecture. The implemented Firewall takes advantage of inherent structure and redundancy of rule set by using our DCFL Extended (DCFLE) algorithm. The use of DCFLE algorithm results in both speed and area improvement when it is implemented in hardware. Although we restrict ourselves to standard 5-tuple matching, the architecture supports additional fields. High throughput classification invariably uses Ternary Content Addressable Memory (TCAM) for prefix matching, though TCAM fares poorly in terms of area and power efficiency. Use of TCAM for port range matching is expensive, as the range to prefix conversion results in large number of prefixes leading to storage inefficiency. Extended TCAM (ETCAM) is fast and the most storage efficient solution for range matching. We present for the first time a reconfigurable hardware implementation of ETCAM. We have implemented our Firewall as an embedded system on Virtex-II Pro FPGA based platform, running Linux with the packet classification in hardware. The Firewall was tested in real time with 1 Gbps Ethernet link and 128 sample rules. The packet classification hardware uses a quarter of logic resources and slightly over one third of memory resources of XC2VP30 FPGA. It achieves a maximum classification throughput of 50 million packet/s corresponding to 16 Gbps link rate for the worst case packet size. The Firewall rule update involves only memory re-initialization in software without any hardware change.

A Scalable High Throughput Firewall in FPGA

High end network security applications demand high speed operation and large rule set support. Packet classification is the core functionality that demands high throughput in such applications. This paper proposes a packet classification architecture to meet such high throughput. We have Implemented a Firewall with this architecture in reconfigurable hardware. We propose an extension to Distributed Crossproducting of Field Labels (DCFL) technique to achieve scalable and high performance architecture. The implemented Firewall takes advantage of inherent structure and redundancy of rule set by using, our DCFL Extended (DCFLE) algorithm. The use of DCFLE algorithm results In both speed and area Improvement when It is Implemented in hardware. Although we restrict ourselves to standard 5-tuple matching, the architecture supports additional fields.High throughput classification Invariably uses Ternary Content Addressable Memory (TCAM) for prefix matching, though TCAM fares poorly In terms of area and power efficiency. Use of TCAM for port range matching is expensive, as the range to prefix conversion results in large number of prefixes leading to storage inefficiency. Extended TCAM (ETCAM) is fast and the most storage efficient solution for range matching. We present for the first time a reconfigurable hardware Implementation of ETCAM. We have implemented our Firewall as an embedded system on Virtex-II Pro FPGA based platform, running Linux with the packet classification in hardware. The Firewall was tested in real time with 1 Gbps Ethernet link and 128 sample rules. The packet classification hardware uses a quarter of logic resources and slightly over one third of memory resources of XC2VP30 FPGA. It achieves a maximum classification throughput of 50 million packet/s corresponding to 16 Gbps link rate for file worst case packet size. The Firewall rule update Involves only memory re-initialiization in software without any hardware change.