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.

Detection,amplification and sequence homology of sodC in clinical isolates of Salmonella sp

Background & objectives: Periplasmic copper and zinc superoxide dismutase (Cu,Zn-SOD or SodC) is an important component of the antioxidant shield which protects bacteria from the phagocytic oxidative burst. Cu,Zn-SODs protect Gram-negative bacteria against oxygen damage which have also been shown to contribute to the pathogenicity of these bacterial species. We report the presence of SodC in drug resistant Salmonella sp. isolated from patients suffering from enteric fever. Further sodC was amplified, cloned into Escherichia coli and the nucleotide sequence and amino acid sequence homology were compared with the standard strain Salmonella Typhimurium 14028. Methods: Salmonella enterica serovar Typhi (S. Typhi) and Salmonellaenterica serovar Paratyphi (S. Paratyphi) were isolated and identified from blood samples of the patients. The isolates were screened for the presence of Cu, Zn-SOD by PAGE using KCN as inhibitor of Cu,Zn-SOD. The gene (sodC) was amplified by PCR, cloned and sequenced. The nucleotide and amino acid sequences of sodC were compared using CLUSTAL X.Results: SodC was detected in 35 per cent of the Salmonella isolates. Amplification of the genomic DNA of S. Typhi and S. Paratyphi with sodC specific primers resulted in 519 and 515 bp amplicons respectively. Single mutational difference at position 489 was observed between thesodC of S. Typhi and S. Paratyphi while they differed at 6 positions with the sodC of S. Typhimurium 14028. The SodC amino acid sequences of the two isolates were homologous but 3 amino acid difference was observed with that of standard strain S. Typhimurium 14028.Interpretation & conclusions: The presence of SodC in pathogenic bacteria could be a novel candidate as phylogenetic marker.

Detection of multiple source locations using a glowworm metaphor with applications to collective robotics

This paper presents a glowworm swarm based algorithm that finds solutions to optimization of multiple optima continuous functions. The algorithm is a variant of a well known ant-colony optimization (ACO) technique, but with several significant modifications. Similar to how each moving region in the ACO technique is associated with a pheromone value, the agents in our algorithm carry a luminescence quantity along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luminescence and have a circular sensor range. The glowworms depend on a local-decision domain to compute their movements. Simulations demonstrate the efficacy of the proposed glowworm based algorithm in capturing multiple optima of a multimodal function. The above optimization scenario solves problems where a collection of autonomous robots is used to form a mobile sensor network. In particular, we address the problem of detecting multiple sources of a general nutrient profile that is distributed spatially on a two dimensional workspace using multiple robots.

Part I: Enzyme replacement versus neurotrophic factor viral vector-mediated gene therapy of Parkinson’s disease, Part II: The effects of orally dosed tolcapone and entacapone on dopamine metabolism in the dorsal striatum and nucleus accumbens in rats

Part I: Parkinson’s disease is a slowly progressive neurodegenerative disorder in which particularly the dopaminergic neurons of the substantia nigra pars compacta degenerate and die. Current conventional treatment is based on restraining symptoms but it has no effect on the progression of the disease. Gene therapy research has focused on the possibility of restoring the lost brain function by at least two means: substitution of critical enzymes needed for the synthesis of dopamine and slowing down the progression of the disease by supporting the functions of the remaining nigral dopaminergic neurons by neurotrophic factors. The striatal levels of enzymes such as tyrosine hydroxylase, dopadecarboxylase and GTP-CH1 are decreased as the disease progresses. By replacing one or all of the enzymes, dopamine levels in the striatum may be restored to normal and behavioral impairments caused by the disease may be ameliorated especially in the later stages of the disease. The neurotrophic factors glial cell derived neurotrophic factor (GDNF) and neurturin have shown to protect and restore functions of dopaminergic cell somas and terminals as well as improve behavior in animal lesion models. This therapy may be best suited at the early stages of the disease when there are more dopaminergic neurons for neurotrophic factors to reach. Viral vector-mediated gene transfer provides a tool to deliver proteins with complex structures into specific brain locations and provides long-term protein over-expression. Part II: The aim of our study was to investigate the effects of two orally dosed COMT inhibitors entacapone (10 and 30 mg/kg) and tolcapone (10 and 30 mg/kg) with a subsequent administration of a peripheral dopadecarboxylase inhibitor carbidopa (30 mg/kg) and L- dopa (30 mg/kg) on dopamine and its metabolite levels in the dorsal striatum and nucleus accumbens of freely moving rats using dual-probe in vivo microdialysis. Earlier similarly designed studies have only been conducted in the dorsal striatum. We also confirmed the result of earlier ex vivo studies regarding the effects of intraperitoneally dosed tolcapone (30 mg/kg) and entacapone (30 mg/kg) on striatal and hepatic COMT activity. The results obtained from the dorsal striatum were generally in line with earlier studies, where tolcapone tended to increase dopamine and DOPAC levels and decrease HVA levels. Entacapone tended to keep striatal dopamine and HVA levels elevated longer than in controls and also tended to elevate the levels of DOPAC. Surprisingly in the nucleus accumbens, dopamine levels after either dose of entacapone or tolcapone were not elevated. Accumbal DOPAC levels, especially in the tolcapone 30 mg/kg group, were elevated nearly to the same extent as measured in the dorsal striatum. Entacapone 10 mg/kg elevated accumbal HVA levels more than the dose of 30 mg/kg and the effect was more pronounced in the nucleus accumbens than in the dorsal striatum. This suggests that entacapone 30 mg/kg has minor central effects. Also our ex vivo study results obtained from the dorsal striatum suggest that entacapone 30 mg/kg has minor and transient central effects, even though central HVA levels were not suppressed below those of the control group in either brain area in the microdialysis study. Both entacapone and tolcapone suppressed hepatic COMT activity more than striatal COMT activity. Tolcapone was more effective than entacapone in the dorsal striatum. The differences between dopamine and its metabolite levels in the dorsal striatum and nucleus accumbens may be due to different properties of the two brain areas.

Detection of a periodic structure hidden in random background: the role of signal amplitude in the matched filter detection method

The matched filter method for detecting a periodic structure on a surface hidden behind randomness is known to detect up to (r(0)/Lambda) gt;= 0.11, where r(0) is the coherence length of light on scattering from the rough part and 3 is the wavelength of the periodic part of the surface-the above limit being much lower than what is allowed by conventional detection methods. The primary goal of this technique is the detection and characterization of the periodic structure hidden behind randomness without the use of any complicated experimental or computational procedures. This paper examines this detection procedure for various values of the amplitude a of the periodic part beginning from a = 0 to small finite values of a. We thus address the importance of the following quantities: `(a)lambda) `, which scales the amplitude of the periodic part with the wavelength of light, and (r(0))Lambda),in determining the detectability of the intensity peaks.

Characterization of viral proteins ofOryctes baculovirus and comparison between two geographical isolates

BacilliformOryctes baculovirus particles have been visualized in electron micrographs of midgut sections from virus infectedOryctes rhinoceros beetles. Morphologically the Indian isolate (Oryctes baculovirus, KI) resembled the previously reportedOryctes baculovirus, isolate PV505. The constituent proteins of baculovirus KI have been analysed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and by Western blots using polyclonal antibodies raised against the complete viral particles, as probes. A total of forty eight viral proteins have been identified. Fourteen viral proteins were located on the viral envelope. Among the proteins constituting the nucleocapsid, three were located internally within the capsid. A 23.5 kDa protein was tightly associated with viral DNA in the nucleocapsid core. Two envelope and seven capsid proteins stained positive for glycosylation. Comparison between the viral proteins of KI and PV505 revealed differences in SDS-PAGE profiles and glycosylation patterns. Immunoblotting of KI and PV505 proteins with anti KI antiserum demonstrated antigenic differences between the two viral isolates.

A Wavelet based Teager Energy Operator for Spike Detection in Microelectrode Array Recordings

Spike detection in neural recordings is the initial step in the creation of brain machine interfaces. The Teager energy operator (TEO) treats a spike as an increase in the `local' energy and detects this increase. The performance of TEO in detecting action potential spikes suffers due to its sensitivity to the frequency of spikes in the presence of noise which is present in microelectrode array (MEA) recordings. The multiresolution TEO (mTEO) method overcomes this shortcoming of the TEO by tuning the parameter k to an optimal value m so as to match to frequency of the spike. In this paper, we present an algorithm for the mTEO using the multiresolution structure of wavelets along with inbuilt lowpass filtering of the subband signals. The algorithm is efficient and can be implemented for real-time processing of neural signals for spike detection. The performance of the algorithm is tested on a simulated neural signal with 10 spike templates obtained from [14]. The background noise is modeled as a colored Gaussian random process. Using the noise standard deviation and autocorrelation functions obtained from recorded data, background noise was simulated by an autoregressive (AR(5)) filter. The simulations show a spike detection accuracy of 90%and above with less than 5% false positives at an SNR of 2.35 dB as compared to 80% accuracy and 10% false positives reported [6] on simulated neural signals.

On resampling detection and its application to detect image tampering

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.

Transient signal detection using wigner-ville distribution and wavelet denoising

The problem of detecting an unknown transient signal in noise is considered. The SNR of the observed data is first enhanced using wavelet domain filter The output of the wavelet domain filter is then transformed using a Wigner-Ville transform,which separates the spectrum of the observed signal into narrow frequency bands. Each subband signal at the output of the Wigner-ville block is subjected kto wavelet based level dependent denoising (WBLDD)to supress colored noise A weighted sum of the absolute value of outputs of WBLDD is passed through an energy detector, whose output is used as test statistic to take the final decision. By assigning weights proportional to the energy of the corresponding subband signals, the proposed detector approximates a frequency domain matched filter Simulation results are presented to show that the performance of the proposed detector is better than that of the wavelet packet transform based detector.

Pressure sensor based tsunami detection system: A laboratory study

In this paper, we present the study and implementation of a low-cost system to detect the occurrences of tsunamis at significantly smaller laboratory scale. The implementation is easily scalable for real-time deployment. Information reported in this paper includes the experimentally recorded response from the pressure sensor giving an indication as well as an alarm at remote place for the detection of water turbulence similar to the case of tsunami. It has been found that the system developed works very well in the laboratory scale.

Acoustic emission technique for leak detection in an end shield of a pressurised heavy water reactor

This paper discusses a successful application of the Acoustic Emission Technique (AET) for the detection and location of leak paths present on an inaccessible side of an end shield of a Pressurised Heavy Water Reactor (PHWR). The methodology was based on the fact that air- and water-leak AE signals have different characteristic features. Baseline data was generated from a sound end shield of a PHWR for characterising the background noise. A mock-up end shield system with saw-cut leak paths was used to verify the validity of the methodology. It was found that air-leak signals under pressurisation (as low as 3 psi) could be detected by frequency domain analysis. Signals due to air leaks from various locations of defective end shield were acquired and analysed. It was possible to detect and locate leak paths. The presence of detected leak paths was further confirmed by an alternative test.

Detection of Tsunami Wave Generation and Propagation Using Fiber Bragg Grating Sensors

This paper describes the design and development of a Fiber Bragg Grating (FBG) sensor system for monitoring tsunami waves generated in the deep ocean. An experimental setup was designed and fabricated to simulate the generation and propagation of a tsunami wave. The characteristics and efficiency of the developed FBG sensor was evaluated with a standard commercial Digiquartz sensor. For real time monitoring of tsunami waves, FBG sensors bonded to a cantilever is used and the wavelength shifts (Delta lambda(B)) in the reflected spectra resulting from the strain/pressure imparted on the FBGs have been recorded using a high-speed Micron Optics FBG interrogation system. The parameters sensed are the signal burst during tsunami generation and pressure variations at different places as the tsunami wave propagates away from the source of generation. The results obtained were compared with the standard commercial sensor used in tsunami detection. The observations suggest that the FBG sensor was highly sensitive and free from many of the constraints associated with the commercial tsunameter.

Detection of moisture stress by indicator plots — A simulation

The possibility of advanced indication of moisture stress in a crop by small prepared plots with compacted or partially sand-substituted soils is examined by an analytical simulation. A series of soils and three crops are considered for the simulation. The moisture characteristics of the soils are calculated with an available model. Using average potential evapotranspiration values and a simple actual evapotranspiration model, the onset of moisture stress in the natural and indicator plots is calculated for different degrees of sand substitution and compaction. Cases where sand substitution fails are determined. The effect of intervening rainfall and limited root depth on the beginning of moisture stress is investigated.

Narrowband Detection of Acoustic Source in Shallow Ocean using Vector Sensor Array

The problem of narrowband CFAR (constant false alarm rate) detection of an acoustic source at an unknown location in a range-independent shallow ocean is considered. If a target is present, the received signal vector at an array of N sensors belongs to an M-dimensional subspace if N exceeds the number of propagating modes M in the ocean. A subspace detection method which utilises the knowledge of the signal subspace to enhance the detector performance is presented in thisMpaper. It is shown that, for a given number of sensors N, the performance of a detector using a vector sensor array is significantly better than that using a scalar sensor array. If a target is detected, the detector using a vector sensor array also provides a concurrent coarse estimate of the bearing of the target.