Statistical analysis driven optimized deep learning system for intrusion detection

Attackers have developed ever more sophisticated and intelligent ways to hack information and communication technology systems. The extent of damage an individual hacker can carry out upon infiltrating a system is well understood. A potentially catastrophic scenario can be envisaged where a nation-state intercepting encrypted financial data gets hacked. Thus, intelligent cybersecurity systems have become inevitably important for improved protection against malicious threats. However, as malware attacks continue to dramatically increase in volume and complexity, it has become ever more challenging for traditional analytic tools to detect and mitigate threat. Furthermore, a huge amount of data produced by large networks has made the recognition task even more complicated and challenging. In this work, we propose an innovative statistical analysis driven optimized deep learning system for intrusion detection. The proposed intrusion detection system (IDS) extracts optimized and more correlated features using big data visualization and statistical analysis methods (human-in-the-loop), followed by a deep autoencoder for potential threat detection. Specifically, a pre-processing module eliminates the outliers and converts categorical variables into one-hot-encoded vectors. The feature extraction module discard features with null values and selects the most significant features as input to the deep autoencoder model (trained in a greedy-wise manner). The NSL-KDD dataset from the Canadian Institute for Cybersecurity is used as a benchmark to evaluate the feasibility and effectiveness of the proposed architecture. Simulation results demonstrate the potential of our proposed system and its outperformance as compared to existing state-of-the-art methods and recently published novel approaches. Ongoing work includes further optimization and real-time evaluation of our proposed IDS.Comment: To appear in the 9th International Conference on Brain Inspired Cognitive Systems (BICS 2018

Effects of ERP Systems in China: Cultural Influences in the Manufacturing Industry

To gain a competitive advantage in the global market, many Chinese manufacturing firms have invested heavily in implementing Enterprise Resource Planning (ERP) systems. Evidence shows, however, that ERP system use has varied significantly between firms. This study addresses such variances in performance in the Chinese manufacturing context, particularly at a plant level. The Gattiker and Goodhue model was adapted for our investigation incorporating a survey instrument. Data were collected from 59 Chinese manufacturing firms. The data collected were analysed using Structural Equation Modeling in association with the Partial Least Squares technique. The results show that the level of interdependence, differentiation between plants, time elapsed after ERP system implementation, high context communication in the Chinese culture, and personal relationships (guanxi) have significant impacts the performance of on firms that use ERP systems. The results also indicate that a better fit between ERP systems and Chinese culture will lead to a higher performance. Particularly, personal relationships (guanxi) have a positive influence on the use of ERP systems, while high context communication has a negative influence. The findings have significant implications for IS researchers and practitioners in the Chinese social context

Atomic spectrometry updates. Review of advances in elemental speciation

This is the sixth Atomic Spectrometry Update (ASU) to focus specifically on advances in elemental speciation and covers a period of approximately 12 months from December 2012. This review deals with all aspects of the analytical speciation methods developed for: the determination of oxidation states; organometallic compounds; coordination compounds; metal and heteroatom- containing biomolecules, including metalloproteins, proteins, peptides and amino acids; and the use of metal-tagging to facilitate detection via atomic spectrometry. The review does not specifically deal with fractionation, sometimes termed operationally defined speciation. As with all ASU reviews 1-5 the coverage of the topic is confined to those methods that incorporate atomic spectrometry as the measurement technique. However, molecular MS techniques are covered where the use is in parallel or series with atomic spectrometry. As with previous years As and Se speciation continues to dominate current literature. However, research is moving further towards understanding the toxicological and beneficial mechanisms of these two elements. There is also in increase in macromolecular analysis, with a decrease in detection limits for some methodologies, which increases the potential clinical use of the techniques employed. The use of both atomic and molecular spectrometry is well developed in these fields, highlighting the interdisciplinary nature of today's research environment. The trend towards lower cost more rapid analytical methods, often involving non-chromatographic speciation, also continues apace. This journal is © 2014 the Partner Organisations

Universal Conductance Distribution in the Quantum Size Regime

We study the conductance (g) distribution function of an ensemble of isolated conducting rings, with an Aharonov--Bohm flux. This is done in the discrete spectrum limit, i.e., when the inelastic rate, frequency and temperature are all smaller than the mean level spacing. Over a wide range of g the distribution function exhibits universal behavior P(g)\sim g^{-(4+\beta)/3}, where \beta=1 (2) for systems with (without) a time reversal symmetry. The nonuniversal large g tail of this distribution determines the values of high moments.Comment: 13 pages+1 figure, RevTEX

Cryptic sympatric species across the Australian range of the global estuarine invader Ficopomatus enigmaticus (Fauvel, 1923) (Serpulidae, Annelida)

Ficopomatus enigmaticus (Fauvel, 1923) is a reef-building serpulid polychaete that has invaded estuaries worldwide, causing environmental and economic harm. Although Australia has long been suggested as a place of origin for the species, this remains unclear. We tested for genetic patterns across the range of F. enigmaticus in southern Australia, predicting that if the species is an Australian native, it would show evidence of (east-west) phylogeographic patterns often observed in native marine species in southern Australia. Unexpectedly, concordant patterns from mitochondrial (Cyt B) sequencing and nuclear marker (iSSR) profiles suggested the presence of at least three genetic groups (putative species), not distributed simply as “east” or “west”. Two common (and closely related) groups were present across Australia and were often found together in the same aggregations. A third group was only found in southeast Australia and was morphologically similar to F. uschakovi (Pillai, 1960), a species previously reported from tropical areas. The discovery of multiple cryptic species with overlapping ranges means that more work is needed to resolve whether any of the F. enigmaticus sensu lato group has an Australian origin and to determine how they are related to invasive populations of F. enigmaticus elsewhere

Non-invasive prenatal diagnostic test accuracy for fetal sex using cell-free DNA a review and meta-analysis

Background: Cell-free fetal DNA (cffDNA) can be detected in maternal blood during pregnancy, opening the possibility of early non-invasive prenatal diagnosis for a variety of genetic conditions. Since 1997, many studies have examined the accuracy of prenatal fetal sex determination using cffDNA, particularly for pregnancies at risk of an X-linked condition. Here we report a review and meta-analysis of the published literature to evaluate the use of cffDNA for prenatal determination (diagnosis) of fetal sex. We applied a sensitive search of multiple bibliographic databases including PubMed (MEDLINE), EMBASE, the Cochrane library and Web of Science. Results: Ninety studies, incorporating 9,965 pregnancies and 10,587 fetal sex results met our inclusion criteria. Overall mean sensitivity was 96.6% (95% credible interval 95.2% to 97.7%) and mean specificity was 98.9% (95% CI = 98.1% to 99.4%). These results vary very little with trimester or week of testing, indicating that the performance of the test is reliably high. Conclusions: Based on this review and meta-analysis we conclude that fetal sex can be determined with a high level of accuracy by analyzing cffDNA. Using cffDNA in prenatal diagnosis to replace or complement existing invasive methods can remove or reduce the risk of miscarriage. Future work should concentrate on the economic and ethical considerations of implementing an early non-invasive test for fetal sex

The effect of gamma irradiation on the biological properties of intervertebral disc allografts: in vitro and in vivo studies in a beagle model

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Spin texture and magnetoroton excitations at nu=1/3

Neutral spin texture (ST) excitations at nu=1/3 are directly observed for the first time by resonant inelastic light scattering. They are determined to involve two simultaneous spin flips. At low magnetic fields, the ST energy is below that of the magnetoroton minimum. With increasing in-plane magnetic field these mode energies cross at a critical ratio of the Zeeman and Coulomb energies of eta(c)=0.020 +/- 0.001. Surprisingly, the intensity of the ST mode grows with temperature in the range in which the magnetoroton modes collapse. The temperature dependence is interpreted in terms of a competition between coexisting phases supporting different excitations. We consider the role of the ST excitations in activated transport at nu=1/3

Vertex importance extension of betweenness centrality algorithm

Variety of real-life structures can be simplified by a graph. Such simplification emphasizes the structure represented by vertices connected via edges. A common method for the analysis of the vertices importance in a network is betweenness centrality. The centrality is computed using the information about the shortest paths that exist in a graph. This approach puts the importance on the edges that connect the vertices. However, not all vertices are equal. Some of them might be more important than others or have more significant influence on the behavior of the network. Therefore, we introduce the modification of the betweenness centrality algorithm that takes into account the vertex importance. This approach allows the further refinement of the betweenness centrality score to fulfill the needs of the network better. We show this idea on an example of the real traffic network. We test the performance of the algorithm on the traffic network data from the city of Bratislava, Slovakia to prove that the inclusion of the modification does not hinder the original algorithm much. We also provide a visualization of the traffic network of the city of Ostrava, the Czech Republic to show the effect of the vertex importance adjustment. The algorithm was parallelized by MPI (http://www.mpi-forum.org/) and was tested on the supercomputer Salomon (https://docs.it4i.cz/) at IT4Innovations National Supercomputing Center, the Czech Republic.808726