Efficient Regular Expression Pattern Matching for Network Intrusion Detection Systems using Modified Word-based Automata

Network Intrusion Detection Systems (NIDS) intercept the traffic at an organization's network periphery to thwart intrusion attempts. Signature-based NIDS compares the intercepted packets against its database of known vulnerabilities and malware signatures to detect such cyber attacks. These signatures are represented using Regular Expressions (REs) and strings. Regular Expressions, because of their higher expressive power, are preferred over simple strings to write these signatures. We present Cascaded Automata Architecture to perform memory efficient Regular Expression pattern matching using existing string matching solutions. The proposed architecture performs two stage Regular Expression pattern matching. We replace the substring and character class components of the Regular Expression with new symbols. We address the challenges involved in this approach. We augment the Word-based Automata, obtained from the re-written Regular Expressions, with counter-based states and length bound transitions to perform Regular Expression pattern matching. We evaluated our architecture on Regular Expressions taken from Snort rulesets. We were able to reduce the number of automata states between 50% to 85%. Additionally, we could reduce the number of transitions by a factor of 3 leading to further reduction in the memory requirements.

Zero knowledge one time digital signature scheme

In many applications, when communicating with a host, we may or may not be concerned about the privacy of the data but are mainly concerned about the integrity of data being transmitted. This paper presents a simple algorithm based on zero knowledge proof by which the receiver can confirm the integrity of data without the sender having to send the digital signature of the message directly. Also, if the same document is sent across by the same user multiple times, this scheme results in different digital signature each time thus making it a practical one-time signature scheme.

A 16-Gene Signature Distinguishes Anaplastic Astrocytoma from Glioblastoma

Anaplastic astrocytoma (AA; Grade III) and glioblastoma (GBM; Grade IV) are diffusely infiltrating tumors and are called malignant astrocytomas. The treatment regimen and prognosis are distinctly different between anaplastic astrocytoma and glioblastoma patients. Although histopathology based current grading system is well accepted and largely reproducible, intratumoral histologic variations often lead to difficulties in classification of malignant astrocytoma samples. In order to obtain a more robust molecular classifier, we analysed RT-qPCR expression data of 175 differentially regulated genes across astrocytoma using Prediction Analysis of Microarrays (PAM) and found the most discriminatory 16-gene expression signature for the classification of anaplastic astrocytoma and glioblastoma. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. Additionally, validation of the 16-gene signature in multiple independent cohorts revealed that the signature predicted anaplastic astrocytoma and glioblastoma samples with accuracy rates of 99%, 88%, and 92% in TCGA, GSE1993 and GSE4422 datasets, respectively. The protein-protein interaction network and pathway analysis suggested that the 16-genes of the signature identified epithelial-mesenchymal transition (EMT) pathway as the most differentially regulated pathway in glioblastoma compared to anaplastic astrocytoma. In addition to identifying 16 gene classification signature, we also demonstrated that genes involved in epithelial-mesenchymal transition may play an important role in distinguishing glioblastoma from anaplastic astrocytoma.

Photocurrent spectroscopic studies of diketopyrrolopyrrole-based statistical copolymers

Diketopyrrolopyrrole (DPP) containing copolymers have gained a lot of interest in organic optoelectronics with great potential in organic photovoltaics. In this work, DPP based statistical copolymers, with slightly different bandgap energies and a varying fraction of donor-acceptor ratio are investigated using monochromatic photocurrent spectroscopy and Fourier-transform photocurrent spectroscopy (FTPS). The statistical copolymer with a lower DPP fraction, when blended with a fullerene derivative, shows the signature of an inter charge transfer complex state in photocurrent spectroscopy. Furthermore, the absorption spectrum of the blended sample with a lower DPP fraction is seen to change as a function of an external bias, qualitatively similar to the quantum confined Stark effect, from where we estimate the exciton binding energy. The statistical copolymer with a higher DPP fraction shows no signal of the inter charge transfer states and yields a higher external quantum efficiency in a photovoltaic structure. In order to gain insight into the origin of the observed charge transfer transitions, we present theoretical studies using density-functional theory and time-dependent density-functional theory for the two pristine DPP based statistical monomers.

Photocurrent spectroscopic studies of diketopyrrolopyrrole-based statistical copolymers

Diketopyrrolopyrrole (DPP) containing copolymers have gained a lot of interest in organic optoelectronics with great potential in organic photovoltaics. In this work, DPP based statistical copolymers, with slightly different bandgap energies and a varying fraction of donor-acceptor ratio are investigated using monochromatic photocurrent spectroscopy and Fourier-transform photocurrent spectroscopy (FTPS). The statistical copolymer with a lower DPP fraction, when blended with a fullerene derivative, shows the signature of an inter charge transfer complex state in photocurrent spectroscopy. Furthermore, the absorption spectrum of the blended sample with a lower DPP fraction is seen to change as a function of an external bias, qualitatively similar to the quantum confined Stark effect, from where we estimate the exciton binding energy. The statistical copolymer with a higher DPP fraction shows no signal of the inter charge transfer states and yields a higher external quantum efficiency in a photovoltaic structure. In order to gain insight into the origin of the observed charge transfer transitions, we present theoretical studies using density-functional theory and time-dependent density-functional theory for the two pristine DPP based statistical monomers.

Copula-Based Modeling of TMI Brightness Temperature With Rainfall Type

Overland rain retrieval using spaceborne microwave radiometer offers a myriad of complications as land presents itself as a radiometrically warm and highly variable background. Hence, land rainfall algorithms of the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) have traditionally incorporated empirical relations of microwave brightness temperature (Tb) with rain rate, rather than relying on physically based radiative transfer modeling of rainfall (as implemented in the TMI ocean algorithm). In this paper, sensitivity analysis is conducted using the Spearman rank correlation coefficient as benchmark, to estimate the best combination of TMI low-frequency channels that are highly sensitive to the near surface rainfall rate from the TRMM Precipitation Radar (PR). Results indicate that the TMI channel combinations not only contain information about rainfall wherein liquid water drops are the dominant hydrometeors but also aid in surface noise reduction over a predominantly vegetative land surface background. Furthermore, the variations of rainfall signature in these channel combinations are not understood properly due to their inherent uncertainties and highly nonlinear relationship with rainfall. Copula theory is a powerful tool to characterize the dependence between complex hydrological variables as well as aid in uncertainty modeling by ensemble generation. Hence, this paper proposes a regional model using Archimedean copulas, to study the dependence of TMI channel combinations with respect to precipitation, over the land regions of Mahanadi basin, India, using version 7 orbital data from the passive and active sensors on board TRMM, namely, TMI and PR. Studies conducted for different rainfall regimes over the study area show the suitability of Clayton and Gumbel copulas for modeling convective and stratiform rainfall types for the majority of the intraseasonal months. Furthermore, large ensembles of TMI Tb (from the most sensitive TMI channel combination) were generated conditional on various quantiles (25th, 50th, 75th, and 95th) of the convective and the stratiform rainfall. Comparatively greater ambiguity was observed to model extreme values of the convective rain type. Finally, the efficiency of the proposed model was tested by comparing the results with traditionally employed linear and quadratic models. Results reveal the superior performance of the proposed copula-based technique.

Regional flood frequency analysis using kernel- based fuzzy clustering approach

Regionalization approaches are widely used in water resources engineering to identify hydrologically homogeneous groups of watersheds that are referred to as regions. Pooled information from sites (depicting watersheds) in a region forms the basis to estimate quantiles associated with hydrological extreme events at ungauged/sparsely gauged sites in the region. Conventional regionalization approaches can be effective when watersheds (data points) corresponding to different regions can be separated using straight lines or linear planes in the space of watershed related attributes. In this paper, a kernel-based Fuzzy c-means (KFCM) clustering approach is presented for use in situations where such linear separation of regions cannot be accomplished. The approach uses kernel-based functions to map the data points from the attribute space to a higher-dimensional space where they can be separated into regions by linear planes. A procedure to determine optimal number of regions with the KFCM approach is suggested. Further, formulations to estimate flood quantiles at ungauged sites with the approach are developed. Effectiveness of the approach is demonstrated through Monte-Carlo simulation experiments and a case study on watersheds in United States. Comparison of results with those based on conventional Fuzzy c-means clustering, Region-of-influence approach and a prior study indicate that KFCM approach outperforms the other approaches in forming regions that are closer to being statistically homogeneous and in estimating flood quantiles at ungauged sites. Key Points Kernel-based regionalization approach is presented for flood frequency analysis Kernel procedure to estimate flood quantiles at ungauged sites is developed A set of fuzzy regions is delineated in Ohio, USA

Al based ultra-fine eutectic with high room temperature plasticity and elevated temperature strength

Developments of aluminum alloys that can retain strength at and above 250 degrees C present a significant challenge. In this paper we report an ultrafine scale Al-Fe-Ni eutectic alloy with less than 3.5 aa transition metals that exhibits room temperature ultimate tensile strength of similar to 400 MPa with a tensile ductility of 6-8%. The yield stress under compression at 300 degrees C was found to be 150 MPa. We attribute it to the refinement of the microstructure that is achieved by suction casting in copper mold. The characterization using scanning and transmission electron microscopy (SEM and TEM) reveals an unique composite structure that contains the Al-Al3Ni rod eutectic with spacing of similar to 90 nm enveloped by a lamellar eutectic of Al-Al9FeNi (similar to 140 nm). Observation of subsurface deformation under Vickers indentation using bonded interface technique reveals the presence of extensive shear banding during deformation that is responsible for the origin of ductility. The dislocation configuration in Al-Al3Ni eutectic colony indicates accommodation of plasticity in alpha-Al with dislocation accumulation at the alpha-Al/Al3Ni interface boundaries. In contrast the dislocation activities in the intermetallic lamellae are limited and contain set of planner dislocations across the plates. We present a detailed analysis of the fracture surface to rationalize the origin of the high strength and ductility in this class of potentially promising cast alloy. (C) 2015 Elsevier B.V. All rights reserved.

Stable isotopic signature of Southern Ocean deep water CO2 ventilation

The link between atmospheric CO2 level and ventilation state of the deep ocean is poorly understood due to the lack of coherent observations on the partitioning of carbon between atmosphere and ocean. In this Southern Ocean study, we have classified the Southern Ocean into different zones based on its hydrological features and have binned the variability in latitudinal air-CO2 concentration and its isotopic ratios. Together with air-CO2, we analysed the surface water for the isotopic ratios in dissolved inorganic carbon (DIC). Using the binary mixing approach on the isotopic ratio of atmospheric CO2 and its concentration, we identified the delta C-13 value of source CO2. The isotopic composition of source CO2 was around -9.22 +/- 0.26 parts per thousand for the year 2011 and 2012, while a composition of -13.49 +/- 4.07 parts per thousand was registered for the year 2013. We used the delta C-13 of DIC to predict the CO2 composition in air under equilibrium and compared our estimates with actual observations. We suggest that the degeneration of the DIC in presence of warm water in the region was the factor responsible for adding the CO2 to the atmosphere above. The place of observation coincides with the zone of high wind speed which promotes the process of CO2 exsolution from sea water. (C) 2015 Elsevier Ltd. All rights reserved.

Phylogenetic analysis of the family Thermaceae with an emphasis on signature position and secondary structure of 16S rRNA

The sequences of the 16S rRNA genes from 38 strains of the family Thermaceae were compared by alignment analysis. The genus-specific and species-specific base substitutions or base deletions (signature positions) were found in three hypervariable regions (in the helices 6, 10 and 17). The differentiation of secondary structures of the high variable regions in the 5' end (38-497) containing several signature positions further supported the concept. Based on the comparisons of the secondary structures in the segments of 16S rRNAs, a key to the species of the family Thermaceae was proposed. (C) 2003 Published by Elsevier Science B.V. on behalf of the Federation of European Microbiological Societies.

Stall warning by blade pressure signature analysis

At low mass flow rates axial compressors suffer from flow instabilities leading to stall and surge. The inception process of these instabilities has been widely researched in the past - primarily with the aim of predicting or averting stall onset. In recent times, attention has shifted to conditions well before stall and has focussed on the level of irregularity in the blade passing signature in the rotor tip region. In general, this irregularity increases in intensity as the flow rate through the compressor is reduced. Attempts have been made to develop stall warning/avoidance procedures based on the level of the flow irregularity, but little effort has been made to characterise the irregularity, or to understand its underlying causes. Work on this project has revealed for the first time that the increase in irregularity in the blade passing signature is highly dependent on both tip-clearance and eccentricity. In a compressor with small, uniform, tip-clearance, the increase in blade passing irregularity which accompanies a reduction in flow rate will be modest. If the tip-clearance is enlarged, however, there will be a sharp rise in irregularity at all circumferential locations. In a compressor with eccentric tip-clearance, the increase in irregularity will only occur in the part of the annulus where the tip-clearance is largest, regardless of the average clearance level. In this paper, some attention is also given to the question of whether this irregularity observed in the pre-stall flow field is due to random turbulence, or to some form of coherent flow structure. Detailed flow measurements reveal that the latter is the case. From these findings, it is clear that a stall warning system based on blade passing signature irregularity will not be viable in an aero-engine where tip-clearance size and eccentricity change during each flight cycle and over the life of the compressor. Copyright © 2011 by ASME.

Stall Warning by Blade Pressure Signature Analysis

At low mass flow rates, axial compressors suffer from flow instabilities leading to stall and surge. The inception process of these instabilities has been widely researched in the past---primarily with the aim of predicting or averting stall onset. In recent times, attention has shifted to conditions well before stall and has focused on the level of irregularity in the blade passing signature in the rotor tip region. In general, the irregularity increases in intensity as the flow rate through the compressor is reduced. Attempts have been made to develop stall warning/avoidance procedures based on the level of flow irregularity, but little effort has been made to characterize the irregularity itself, or to understand its underlying cause. Work on this project has revealed for the first time that the increase in irregularity in the blade passing signature is highly dependent on both tip-clearance size and eccentricity. In a compressor with small, uniform, tip-clearance, the increase in blade passing irregularity that accompanies a reduction in flow rate will be modest. If the tip-clearance is enlarged, however, there will be a sharp rise in irregularity at all circumferential locations. In a compressor with eccentric tip-clearance, the increase in irregularity will only occur in the part of the annulus where the tip-clearance is largest, regardless of the average clearance level. In this paper, some attention is also given to the question of whether the irregularity observed in the prestall flow field is due to random turbulence or to some form of coherent flow structure. Detailed flow measurements reveal that the latter is the case. From these findings, it is clear that a stall warning system based on blade passing signature irregularity would be difficult to implement in an aero-engine where tip-clearance size and eccentricity change during each flight cycle and over the life of the compressor. © 2013 American Society of Mechanical Engineers.

A body force-based method for prediction of multiple-pure-tone noise: Validation

Emissions, fuel burn, and noise are the main drivers for innovative aircraft design. Embedded propulsion systems, such as for example used in hybrid-wing body aircraft, can offer fuel burn and noise reduction benefits but the impact of inlet flow distortion on the generation and propagation of turbomachinery noise has yet to be assessed. A novel approach is used to quantify the effects of non-uniform flow on the creation and propagation of multiple pure tone (MPT) noise. The ultimate goal is to conduct a parametric study of S-duct inlets to quantify the effects of inlet design parameters on the acoustic signature. The key challenge is that the effects of distortion transfer, noise source generation and propagation through the non-uniform flow field are inherently coupled such that a simultaneous computation of the aerodynamics and acoustics is required to capture the mechanisms at play. The technical approach is based on a body force description of the fan blade row that is able to capture the distortion transfer and the blade-to-blade flow variations that cause the MPT noise while reducing computational cost. A single, 3-D full-wheel CFD simulation, in which the Euler equations are solved to second-order spatial and temporal accuracy, simultaneously computes the MPT noise generation and its propagation in distorted inlet flow. A new method of producing the blade-to-blade variations in the body force field for MPT noise generation has been developed and validated. The numerical dissipation inherent to the solver is quantified and used to correct for non-physical attenuation in the far-field noise spectra. Source generation, acoustic propagation and acoustic energy transfer between modes is examined in detail. The new method is validated on NASA's Source Diagnostic Test fan and inlet, showing good agreement with experimental data for aerodynamic performance, acoustic source generation, and far-field noise spectra. The next steps involve the assessment of MPT noise in serpentine inlet ducts and the development of a reduced order formulation suitable for incorporation into NASA's ANOPP framework. © 2010 by Jeff Defoe, Alex Narkaj & Zoltan Spakovszky.

Determining vibration signature of a defective planet bearing in a wind turbine epicyclic gearbox

Planet bearings of wind turbine epicyclic gearboxes are considered as one of the most critical components due to their high failure rate. In order to develop effective vibration based detection algorithms for these bearings, a thorough understanding of their vibration signature is required. In this paper, we investigate the vibration behaviour of an epicyclic gearbox in the presence of a defective planet bearing both theoretically and experimentally. We also identify different sources of modulation sidebands using an analytical model which includes ring gear flexibility and planet bearing defects. The findings from this work will help engineers to develop more effective fault detection algorithms.

Waveguide based compact silicon Schottky photodetector with enhanced responsivity in the telecom spectral band.

We experimentally demonstrate an on-chip compact and simple to fabricate silicon Schottky photodetector for telecom wavelengths operating on the basis of internal photoemission process. The device is realized using CMOS compatible approach of local-oxidation of silicon, which enables the realization of the photodetector and low-loss bus photonic waveguide at the same fabrication step. The photodetector demonstrates enhanced internal responsivity of 12.5mA/W for operation wavelength of 1.55µm corresponding to an internal quantum efficiency of 1%, about two orders of magnitude higher than our previously demonstrated results [22]. We attribute this improved detection efficiency to the presence of surface roughness at the boundary between the materials forming the Schottky contact. The combination of enhanced quantum efficiency together with a simple fabrication process provides a promising platform for the realization of all silicon photodetectors and their integration with other nanophotonic and nanoplasmonic structures towards the construction of monolithic silicon opto-electronic circuitry on-chip.