Analysis of Intelligent Classifiers and Enhancing the Detection Accuracy for Intrusion Detection System

In this paper we discuss and analyze some of the intelligent classifiers which allows for automatic detection and classification of networks attacks for any intrusion detection system. We will proceed initially with their analysis using the WEKA software to work with the classifiers on a well-known IDS (Intrusion Detection Systems) dataset like NSL-KDD dataset. The NSL-KDD dataset of network attacks was created in a military network by MIT Lincoln Labs. Then we will discuss and experiment some of the hybrid AI (Artificial Intelligence) classifiers that can be used for IDS, and finally we developed a Java software with three most efficient classifiers and compared it with other options. The outputs would show the detection accuracy and efficiency of the single and combined classifiers used

Quantitative utilization of prior biological knowledge in the Bayesian network modeling of gene expression data

<p>Abstract</p> <p>Background</p> <p>Bayesian Network (BN) is a powerful approach to reconstructing genetic regulatory networks from gene expression data. However, expression data by itself suffers from high noise and lack of power. Incorporating prior biological knowledge can improve the performance. As each type of prior knowledge on its own may be incomplete or limited by quality issues, integrating multiple sources of prior knowledge to utilize their consensus is desirable.</p> <p>Results</p> <p>We introduce a new method to incorporate the quantitative information from multiple sources of prior knowledge. It first uses the Naïve Bayesian classifier to assess the likelihood of functional linkage between gene pairs based on prior knowledge. In this study we included cocitation in PubMed and schematic similarity in Gene Ontology annotation. A candidate network edge reservoir is then created in which the copy number of each edge is proportional to the estimated likelihood of linkage between the two corresponding genes. In network simulation the Markov Chain Monte Carlo sampling algorithm is adopted, and samples from this reservoir at each iteration to generate new candidate networks. We evaluated the new algorithm using both simulated and real gene expression data including that from a yeast cell cycle and a mouse pancreas development/growth study. Incorporating prior knowledge led to a ~2 fold increase in the number of known transcription regulations recovered, without significant change in false positive rate. In contrast, without the prior knowledge BN modeling is not always better than a random selection, demonstrating the necessity in network modeling to supplement the gene expression data with additional information.</p> <p>Conclusion</p> <p>our new development provides a statistical means to utilize the quantitative information in prior biological knowledge in the BN modeling of gene expression data, which significantly improves the performance.</p

Smoking prevalence and attributable disease burden in 195 countries and territories, 1990-2015 : a systematic analysis from the Global Burden of Disease Study 2015

Background The scale-up of tobacco control, especially after the adoption of the Framework Convention for Tobacco Control, is a major public health success story. Nonetheless, smoking remains a leading risk for early death and disability worldwide, and therefore continues to require sustained political commitment. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) offers a robust platform through which global, regional, and national progress toward achieving smoking-related targets can be assessed. Methods We synthesised 2818 data sources with spatiotemporal Gaussian process regression and produced estimates of daily smoking prevalence by sex, age group, and year for 195 countries and territories from 1990 to 2015. We analysed 38 risk-outcome pairs to generate estimates of smoking-attributable mortality and disease burden, as measured by disability-adjusted life-years (DALYs). We then performed a cohort analysis of smoking prevalence by birth-year cohort to better understand temporal age patterns in smoking. We also did a decomposition analysis, in which we parsed out changes in all-cause smoking-attributable DALYs due to changes in population growth, population ageing, smoking prevalence, and risk-deleted DALY rates. Finally, we explored results by level of development using the Socio-demographic Index (SDI). Findings Worldwide, the age-standardised prevalence of daily smoking was 25.0% (95% uncertainty interval [UI] 24.2-25.7) for men and 5.4% (5.1-5.7) for women, representing 28.4% (25.8-31.1) and 34.4% (29.4-38.6) reductions, respectively, since 1990. A greater percentage of countries and territories achieved significant annualised rates of decline in smoking prevalence from 1990 to 2005 than in between 2005 and 2015; however, only four countries had significant annualised increases in smoking prevalence between 2005 and 2015 (Congo [Brazzaville] and Azerbaijan for men and Kuwait and Timor-Leste for women). In 2015, 11.5% of global deaths (6.4 million [95% UI 5.7-7.0 million]) were attributable to smoking worldwide, of which 52.2% took place in four countries (China, India, the USA, and Russia). Smoking was ranked among the five leading risk factors by DALYs in 109 countries and territories in 2015, rising from 88 geographies in 1990. In terms of birth cohorts, male smoking prevalence followed similar age patterns across levels of SDI, whereas much more heterogeneity was found in age patterns for female smokers by level of development. While smoking prevalence and risk-deleted DALY rates mostly decreased by sex and SDI quintile, population growth, population ageing, or a combination of both, drove rises in overall smoking-attributable DALYs in low-SDI to middle-SDI geographies between 2005 and 2015. Interpretation The pace of progress in reducing smoking prevalence has been heterogeneous across geographies, development status, and sex, and as highlighted by more recent trends, maintaining past rates of decline should not be taken for granted, especially in women and in low-SDI to middle-SDI countries. Beyond the effect of the tobacco industry and societal mores, a crucial challenge facing tobacco control initiatives is that demographic forces are poised to heighten smoking's global toll, unless progress in preventing initiation and promoting cessation can be substantially accelerated. Greater success in tobacco control is possible but requires effective, comprehensive, and adequately implemented and enforced policies, which might in turn require global and national levels of political commitment beyond what has been achieved during the past 25 years.Peer reviewe

Search for contact interactions and large extra dimensions in the dilepton mass spectra from proton-proton collisions at \sqrt{s} = 13 TeV

A search for nonresonant excesses in the invariant mass spectra of electron and muon pairs is presented. The analysis is based on data from proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the CMS experiment in 2016, corresponding to a total integrated luminosity of 36 fb^{-1}. No significant deviation from the standard model is observed. Limits are set at 95% confidence level on energy scales for two general classes of nonresonant models. For a class of fermion contact interaction models, lower limits ranging from 20 to 32 TeV are set on the characteristic compositeness scale Λ. For the Arkani-Hamed, Dimopoulos, and Dvali model of large extra dimensions, the first results in the dilepton final state at 13 TeV are reported, and values of the ultraviolet cutoff parameter Λ_{T} below 6.9 TeV are excluded. A combination with recent CMS diphoton results improves this exclusion to Λ_{T} below 7.7 TeV, providing the most sensitive limits to date in nonhadronic final states

Measurement of the WZ production cross section in pp collisions at root s=13 Tev

Peer reviewe

Relative Modification of Prompt psi(2S) and J/psi Yields from pp to PbPb Collisions at root(S)(NN)=5.02 TeV

Peer reviewe

Studies of B_{s2}^{*} (5840)⁰ and B_{s1} (5830)⁰ mesons including the observation of the B_{s2}^{*} (5840)⁰ → B⁰K_{s}^{0} decay in proton-proton collisions at √s = 8 TeV

Measurements of B_{s2}^{*} (5840)⁰ and B_{s1} (5840)⁰ mesons are performed using a data sample of proton-proton collisions corresponding to an integrated luminosity of 19.6 fb⁻¹, collected with the CMS detector at the LHC at a centre-of-mass energy of 8 TeV. The analysis studies P-wave B_{s}^{0} meson decays into B^{(*)}⁺K⁻ and B^{(*)}⁰K_{s}^{0}, where the B⁺ and B⁰ mesons are identified using the decays B⁺ → J/φK⁺ and B⁰ → J/φK* (892)⁰. The masses of the P-wave B_{s}^{0} meson states are measured and the natural width of the B_{*}^{s2} (5840)⁰ state is determined. The first measurement of the mass difference between the charged and neutral B* mesons is also presented. The B_{*}^{s2} (5840)⁰ decay to B⁰K_{s}^{0} is observed, together with a measurement of its branching fraction relative to the B_{s2}^{*} (5840)⁰ → B⁺K⁻ decay

Search for resonant tt¯ production in proton-proton collisions at s√=13 TeV

A search for a heavy resonance decaying into a top quark and antiquark (tt¯) pair is performed using proton-proton collisions at s√=13 TeV. The search uses the data set collected with the CMS detector in 2016, which corresponds to an integrated luminosity of 35.9 fb−1. The analysis considers three exclusive final states and uses reconstruction techniques that are optimized for top quarks with high Lorentz boosts, which requires the use of nonisolated leptons and jet substructure techniques. No significant excess of events relative to the expected yield from standard model processes is observed. Upper limits on the production cross section of heavy resonances decaying to a tt¯ pair are calculated. Limits are derived for a leptophobic topcolor Z′ resonance with widths of 1, 10, and 30%, relative to the mass of the resonance, and exclude masses up to 3.80, 5.25, and 6.65 TeV, respectively. Kaluza-Klein excitations of the gluon in the Randall-Sundrum model are excluded up to 4.55 TeV. To date, these are the most stringent limits on tt¯ resonances

Search for excited leptons in final states in proton-proton collisions at root s=13 TeV

A search is presented for excited electrons and muons in ℓℓγ final states at the LHC. The search is based on a data sample corresponding to an integrated luminosity of 35.9 fb−1 of proton-proton collisions at a center-of-mass energy of 13 TeV, collected with the CMS detector in 2016. This is the first search for excited leptons at s√ = 13 TeV. The observation is consistent with the standard model background prediction, and the most stringent exclusion limits to date are set on the excited lepton mass and the compositeness scale, at 95% confidence level. Excited electrons and muons are excluded for masses below 3.9 and 3.8 TeV, respectively, under the assumption that the excited lepton mass equals the compositeness scale. The best observed limit on the compositeness scale is obtained with an excited lepton mass of around 1.0 TeV, excluding values below 25 TeV for both excited electrons and muons