Improvement in Intrusion Detection With Advances in Sensor Fusion

Various intrusion detection systems (IDSs) reported in the literature have shown distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on the other classes. In view of the enormous computing power available in the present-day processors, deploying multiple IDSs in the same network to obtain best-of-breed solutions has been attempted earlier. The paper presented here addresses the problem of optimizing the performance of IDSs using sensor fusion with multiple sensors. The trade-off between the detection rate and false alarms with multiple sensors is highlighted. It is illustrated that the performance of the detector is better when the fusion threshold is determined according to the Chebyshev inequality. In the proposed data-dependent decision ( DD) fusion method, the performance optimization of ndividual IDSs is first addressed. A neural network supervised learner has been designed to determine the weights of individual IDSs depending on their reliability in detecting a certain attack. The final stage of this DD fusion architecture is a sensor fusion unit which does the weighted aggregation in order to make an appropriate decision. This paper theoretically models the fusion of IDSs for the purpose of demonstrating the improvement in performance, supplemented with the empirical evaluation.

A single point mutation disrupts the capsid assembly in Sesbania Mosaic Virus resulting in a stable isolated dimer

Protein-protein interactions play a Crucial role in Virus assembly and stability. With the view of disrupting capsid assembly and capturing smaller oligomers, interfacial residue mutations were carried Out in the coat protein gene of Sesbania Mosaic Virus, a T=3 ss (+) RNA plant virus. A single point mutation of a Trp 170 present at the five-fold interface of the virus to a charged residue (Glu or Lys) arrested assembly of virus like particles and resulted in stable Soluble dimers of the capsid Protein. The X-ray crystal structure of one of the isolated dimer mutants - rCP Delta N65W170K was determined to a resolution of 2.65 angstrom. Detailed analysis of the dimeric mutant protein structure revealed that a number of Structural changes take place, especially in the loop and interfacial regions during the course of assembly. The isolated chiller was ``more relaxed'' than the dimer found in the T=3 or T=1 capsids. The isolated dimer does not bind Ca2+ ion and consequently four C-terminal residues are disordered. The FG loop, which interacts with RNA in the Virus, has different conformations in the isolated dimer and the intact Virus Suggesting its flexible nature and the conformational changes that accompany assembly. The isolated choler mutant was much less stable when compared to the assembled capsids, suggesting the importance of inter-subunit interactions and Ca2+ mediated interactions in the stability of the capsids. With this study, SeMV becomes the first icosahedral virus for which X-ray crystal Structures of T=3, T=1 capsids as well as a smaller oligomer of the capsid protein have been determined.

A thymine-related mutation system in immunoglobulin variable regions

Abstract is not available.

BRCA1 and BRCA2 germline mutation analysis among Indian women from south India: identification of four novel mutations and high-frequency occurrence of 185delAG mutation

Mutations in the BRCA1 and BRCA2 genes profoundly increase the risk of developing breast and/or ovarian cancer among women. To explore the contribution of BRCA1 and BRCA2 mutations in the development of hereditary breast cancer among Indian women, we carried out mutation analysis of the BRCA1 and BRCA2 genes in 61 breast or ovarian cancer patients from south India with a positive family history of breast and/or ovarian cancer. Mutation analysis was carried out using conformation-sensitive gel electrophoresis (CSGE) followed by sequencing. Mutations were identified in 17 patients (28.0%); 15 (24.6%) had BRCA1 mutations and two (3.28%) had BRCA2 mutations. While no specific association between BRCA1 or BRCA2 mutations with cancer type was seen, mutations were more often seen in families with ovarian cancer. While 40% (4/10) and 30.8% (4/12) of families with ovarian or breast and ovarian cancer had mutations, only 23.1% (9/39) of families with breast cancer carried mutations in the BRCA1 and BRCA2 genes. In addition, while BRCA1 mutations were found in all age groups, BRCA2 mutations were found only in the age group of <= 40 years. Of the BRCA1 mutations, there were three novel mutations (295delCA; 4213T -> A; 5267T -> G) G) and three mutations that have been reported earlier. Interestingly, 185delAG, a BRCA1 mutation which occurs at a very high frequency in Ashkenazi Jews, was found at a frequency of 16.4% (10/61). There was one novel mutation (4866insT) and one reported mutation in BRCA2. Thus, our study emphasizes the importance of mutation screening in familial breast and/or ovarian cancers, and the potential implications of these findings in genetic counselling and preventive therapy.

Acoustic emission source location and damage detection in a metallic structure using a graph-theory-based geodesic pproach

A geodesic-based approach using Lamb waves is proposed to locate the acoustic emission (AE) source and damage in an isotropic metallic structure. In the case of the AE (passive) technique, the elastic waves take the shortest path from the source to the sensor array distributed in the structure. The geodesics are computed on the meshed surface of the structure using graph theory based on Dijkstra's algorithm. By propagating the waves in reverse virtually from these sensors along the geodesic path and by locating the first intersection point of these waves, one can get the AE source location. The same approach is extended for detection of damage in a structure. The wave response matrix of the given sensor configuration for the healthy and the damaged structure is obtained experimentally. The healthy and damage response matrix is compared and their difference gives the information about the reflection of waves from the damage. These waves are backpropagated from the sensors and the above method is used to locate the damage by finding the point where intersection of geodesics occurs. In this work, the geodesic approach is shown to be suitable to obtain a practicable source location solution in a more general set-up on any arbitrary surface containing finite discontinuities. Experiments were conducted on aluminum specimens of simple and complex geometry to validate this new method.

A Proof of Convergence of the B-RED and P-RED Algorithms for Random Early Detection

In [8], we recently presented two computationally efficient algorithms named B-RED and P-RED for random early detection. In this letter, we present the mathematical proof of convergence of these algorithms under general conditions to local minima.

Selective detection of single-enantiomer spectrum of chiral molecules aligned in the polypeptide liquid crystalline solvent: Transition selective one-dimensional H-1-H-1 COSY

One-dimensional (1D) proton NMR spectra of enantiomers are generally undecipherable in chiral orienting poly-gamma-benzyl-L-glutamate (PBLG)/CDCl3 solvent. This arises due to large number of couplings, in addition to superposition of spectra from both the enantiomers, severely hindering the H-1 detection. On the other hand in the present study the benefit is derived front the presence of several couplings among the entire network of interacting protons. Transition selective 1D H-1-H-1 correlation experiment (1D-COSY) which utilizes the Coupling assisted transfer of magnetization not only for unraveling the overlap but also for the selective detection of enantiopure spectrum is reported. The experiment is simple, easy to implement and provides accurate eanantiomeric excess in addition to the determination of the proton-proton couplings of an enantiomer within a short experimental time (few minutes). (C) 2009 Elsevier Inc. All rights reserved.

High-Rate Space-Time Coded Large-MIMO Systems: Low-Complexity Detection and Channel Estimation

In this paper, we present a low-complexity algorithm for detection in high-rate, non-orthogonal space-time block coded (STBC) large-multiple-input multiple-output (MIMO) systems that achieve high spectral efficiencies of the order of tens of bps/Hz. We also present a training-based iterative detection/channel estimation scheme for such large STBC MIMO systems. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed multistage likelihood ascent search (M-LAS) detector in conjunction with the proposed iterative detection/channel estimation scheme at low complexities. The fact that we could show such good results for large STBCs like 16 X 16 and 32 X 32 STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot based training for channel estimation and turbo coding) establishes the effectiveness of the proposed detector and channel estimator. We decode perfect codes of large dimensions using the proposed detector. With the feasibility of such a low-complexity detection/channel estimation scheme, large-MIMO systems with tens of antennas operating at several tens of bps/Hz spectral efficiencies can become practical, enabling interesting high data rate wireless applications.

Detection of microorganisms using biosensors-a smarter way towards detection techniques.

Along with useful microorganisms, there are some that cause potential damage to the animals and plants. Detection and identification of these harmful organisms in a cost and time effective way is a challenge for the researchers. The future of detection methods for microorganisms shall be guided by biosensor, which has already contributed enormously in sensing and detection technology. Here, we aim to review the use of various biosensors, developed by integrating the biological and physicochemical/mechanical properties (of tranducers), which can have enormous implication in healthcare, food, agriculture and biodefence. We have also highlighted the ways to improve the functioning of the biosensor.

A distinct physiological role of MutY in mutation prevention in mycobacteria

Oxidative damage to DNA results in the occurrence of 7,8-dihydro-B-oxoguanine (8-oxoG) in the genome. In eubacteria, repair of such damage is initiated by two major base-excision repair enzymes, MutM and MutY. We generated a MutY-deficient strain of Mycobacterium smegmatis to investigate the role of this enzyme in DNA repair. The MutY deficiency in M. smegmatis did not result in either a noteworthy susceptibility to oxidative stress or an increase in the mutation rate. However, rifampicin resistant isolates of the MutY-deficient strain showed distinct mutations in the rifampicin-resistance-determining region of rpoB. Besides the expected C to A (or G to T) mutations, an increase in A to C (or T to G) mutations was also observed. Biochemical characterization of mycobacterial MutY (M. smegmatis and M. tuberculosis) revealed an expected excision of A opposite 8-oxoG in DNA. Additionally, excision of G and T opposite 8-oxoG was detected. MutY formed complexes with DNA containing 8-oxoG: A, 8-oxoG: G or 8-oxoG: T but not 8-oxoG : C pairs. Primer extension reactions in cell-free extracts of M. smegmatis suggested error-prone incorporation of nucleotides into the DNA. Based on these observations, we discuss the physiological role of MutY in specific mutation prevention in mycobacteria.

A Low-Complexity Near-ML Performance Achieving Algorithm for Large MIMO Detection

In this paper, we present a low-complexity, near maximum-likelihood (ML) performance achieving detector for large MIMO systems having tens of transmit and receive antennas. Such large MIMO systems are of interest because of the high spectral efficiencies possible in such systems. The proposed detection algorithm, termed as multistage likelihood-ascent search (M-LAS) algorithm, is rooted in Hopfield neural networks, and is shown to possess excellent performance as well as complexity attributes. In terms of performance, in a 64 x 64 V-BLAST system with 4-QAM, the proposed algorithm achieves an uncoded BER of 10(-3) at an SNR of just about 1 dB away from AWGN-only SISO performance given by Q(root SNR). In terms of coded BER, with a rate-3/4 turbo code at a spectral efficiency of 96 bps/Hz the algorithm performs close to within about 4.5 dB from theoretical capacity, which is remarkable in terms of both high spectral efficiency as well as nearness to theoretical capacity. Our simulation results show that the above performance is achieved with a complexity of just O(NtNt) per symbol, where N-t and N-tau denote the number of transmit and receive antennas.

A method of fraud & intrusion detection for e-payment systems in mobile

The need for paying with mobile devices has urged the development of payment systems for mobile electronic commerce. In this paper we have considered two important abuses in electronic payments systems for detection. The fraud, which is an intentional deception accomplished to secure an unfair gain, and an intrusion which are any set of actions that attempt to compromise the integrity, confidentiality or availability of a resource. Most of the available fraud and intrusion detection systems for e-payments are specific to the systems where they have been incorporated. This paper proposes a generic model called as Activity-Event-Symptoms(AES) model for detecting fraud and intrusion attacks which appears during payment process in the mobile commerce environment. The AES model is designed to identify the symptoms of fraud and intrusions by observing various events/transactions occurs during mobile commerce activity. The symptoms identification is followed by computing the suspicion factors for event attributes, and the certainty factor for a fraud and intrusion is generated using these suspicion factors. We have tested the proposed system by conducting various case studies, on the in-house established mobile commerce environment over wired and wire-less networks test bed.

Block-based feature detection and matching for mosaicing of camera-captured document images

In this paper, we present a new feature-based approach for mosaicing of camera-captured document images. A novel block-based scheme is employed to ensure that corners can be reliably detected over a wide range of images. 2-D discrete cosine transform is computed for image blocks defined around each of the detected corners and a small subset of the coefficients is used as a feature vector A 2-pass feature matching is performed to establish point correspondences from which the homography relating the input images could be computed. The algorithm is tested on a number of complex document images casually taken from a hand-held camera yielding convincing results.

Detection of contiguous and distributed damage through contours of equal frequency change

The paper presents the results of a computational modeling for damage identification process for an axial rod representing an end-bearing pile foundation with known damage and a simply supported beam representing a bridge girder. The paper proposes a methodology for damage identification from measured natural frequencies of a contiguously damaged reinforced concrete axial rod and beam, idealized with distributed damage model. Identification of damage is from Equal_Eigen_value_change (Iso_Eigen_value_Change) contours, plotted between pairs of different frequencies. The performance of the method is checked for a wide variation of damage positions and extents. An experiment conducted on a free-free axially loaded reinforced concrete member and a flexural beam is shown as examples to prove the pros and cons of this method. (C) 2009 Elsevier Ltd. All rights reserved.

Energy efficient change detection over a MAC using physical layer fusion

We propose a simple and energy efficient distributed change detection scheme for sensor networks based on Page's parametric CUSUM algorithm. The sensor observations are IID over time and across the sensors conditioned on the change variable. Each sensor runs CUSUM and transmits only when the CUSUM is above some threshold. The transmissions from the sensors are fused at the physical layer. The channel is modeled as a multiple access channel (MAC) corrupted with IID noise. The fusion center which is the global decision maker, performs another CUSUM to detect the change. We provide the analysis and simulation results for our scheme and compare the performance with an existing scheme which ensures energy efficiency via optimal power selection.