A Novel Approach for Detection of DoS / DDoS Attack in Network Environment using Ensemble Machine Learning Model

One of the most  serious threat to network security is Denial of service (DOS) attacks. Internet and computer networks are now important parts of our businesses and daily lives. Malicious actions have become more common as our reliance on computers and communication networks has grown. Network threats are a big problem in the way people communicate today. To make sure that the networks work well and that users' information is safe, the network data must be watched and analysed to find malicious activities and attacks. Flooding may be the simplest DDoS assault. Computer networks and services are vulnerable to DoS and DDoS attacks. These assaults flood target systems with malicious traffic, making them unreachable to genuine users. The work aims to enhance the resilience of network infrastructures against these attacks and ensure uninterrupted service delivery. This research develops and evaluates enhanced DoS/DDoS detection methods. DoS attacks usually stop or slow down legal computer or network use. Denial-of-service (DoS) attacks prevent genuine users from accessing and using information systems and resources. The OSI model's layers make up the computer network. Different types of DDoS strikes target different layers. The Network Layer can be broken by using ICMP Floods or Smurf Attacks. The Transport layer can be attacked using UDP Floods, TCP Connection Exhaustion, and SYN Floods. HTTP-encrypted attacks can be used to get through to the application layer. DoS/DDoS attacks are malicious attacks. Protect network data from harm. Computer network services are increasingly threatened by DoS/DDoS attacks. Machine learning may detect prior DoS/DDoS attacks. DoS/DDoS attacks proliferate online and via social media. Network security is IT's top priority. DoS and DDoS assaults include ICMP, UDP, and the more prevalent TCP flood attacks. These strikes must be identified and stopped immediately. In this work, a stacking ensemble method is suggested for detecting DoS/DDoS attacks so that our networked data doesn't get any worse. This paper used a method called "Ensemble of classifiers," in which each class uses a different way to learn. In proposed  methodology Experiment#1 , I used the Home Wifi Network Traffic Collected and generated own Dataset named it as MywifiNetwork.csv, whereas in proposed methodology Experiment#2, I used the kaggle repository “NSL-KDD benchmark dataset” to perform experiments in order to find detection accuracy of dos attack detection using python language in jupyter notebook. The system detects attack-type or legitimate-type of network traffic during detection ML classification methods are used to compare how well the suggested system works. The results show that when the ensembled stacking learning model is used, 99% of the time it is able to find the problem. In proposed methodology two Experiments are implemented for comparing detection accuracy with the existing techniques. Compared to other measuring methods, we get a big step forward in finding attacks. So, our model gives a lot of faith in securing these networks. This paper will analyse the behaviour of network traffics

Neutron Diffraction Studies on La2-xDyxCa2xBa2Cu4+2xOz Superconductors

Structural studies on Dy-substituted La-2125 type superconductors have been carried out by neutron diffraction experiments at room temperature using a monochromatic neutron beam of wavelength lambda = 1.249 Angstroms. A series of samples with La2-xDyxCa2xBa2Cu4+2xOz stoichiometric composition, for x = 0.1 - 0.5, have been studied for their structural properties. A tetragonal Y-123 unit cell was taken as the starting model for the Rietveld analysis. All the samples fit into the starting model, exhibiting no structural transition taking place with increasing dopant concentration. The results of Rietveld analysis and structural properties are discussed in detail

The Ascomycete Verticillium longisporum Is a Hybrid and a Plant Pathogen with an Expanded Host Range

Hybridization plays a central role in plant evolution, but its overall importance in fungi is unknown. New plant pathogens are thought to arise by hybridization between formerly separated fungal species. Evolution of hybrid plant pathogens from non-pathogenic ancestors in the fungal-like protist Phytophthora has been demonstrated, but in fungi, the most important group of plant pathogens, there are few well-characterized examples of hybrids. We focused our attention on the hybrid and plant pathogen Verticillium longisporum, the causal agent of the Verticillium wilt disease in crucifer crops. In order to address questions related to the evolutionary origin of V. longisporum, we used phylogenetic analyses of seven nuclear loci and a dataset of 203 isolates of V. longisporum, V. dahliae and related species. We confirmed that V. longisporum was diploid, and originated three different times, involving four different lineages and three different parental species. All hybrids shared a common parent, species A1, that hybridized respectively with species D1, V. dahliae lineage D2 and V. dahliae lineage D3, to give rise to three different lineages of V. longisporum. Species A1 and species D1 constituted as yet unknown taxa. Verticillium longisporum likely originated recently, as each V. longisporum lineage was genetically homogenous, and comprised species A1 alleles that were identical across lineages

Finding needles in haystacks:Linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Reannotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi.The Intramural Research Programs of the National Center for Biotechnology Information, National Library of Medicine and the National Human Genome Research Institute, both at the National Institutes of Health.http://www.ncbi.nlm.nih.gov/bioproject/PRJNA177353am201

Finding needles in haystacks : linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Reannotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi.The Intramural Research Programs of the National Center for Biotechnology Information, National Library of Medicine and the National Human Genome Research Institute, both at the National Institutes of Health.http://www.ncbi.nlm.nih.gov/bioproject/PRJNA177353am201

Analysis of PAPR in OTFS modulation with classical selected mapping technique

Abstract Orthogonal Time Frequency Space (OTFS) is the advanced stage of modulation for this fast-growing generation. This is the waveform proposed to be used in next-generation communication systems i.e., 6G, as it has the advantage of high data rate, better flexibility, requires a less cyclic prefix and less amount of peak to average power ratio (PAPR) compared to Orthogonal Frequency Division Multiplexing (OFDM). To reduce the amount of PAPR in the OTFS, the best method is the classical selected mapping (SLM) technique. This paper presents the PAPR analysis in OTFS modulation by using classical SLM and the obtained results are compared against the OFDM modulation

Maintenance of Sex-Related Genes and the Co-Occurrence of Both Mating Types in <i>Verticillium dahliae</i>

<div><p><i>Verticillium dahliae</i> is a cosmopolitan, soilborne fungus that causes a significant wilt disease on a wide variety of plant hosts including economically important crops, ornamentals, and timber species. Clonal expansion through asexual reproduction plays a vital role in recurring plant epidemics caused by this pathogen. The recent discovery of recombination between clonal lineages and preliminary investigations of the meiotic gene inventory of <i>V. dahliae</i> suggest that cryptic sex appears to be rare in this species. Here we expanded on previous findings on the sexual nature of <i>V. dahliae</i>. Only 1% of isolates in a global collection of 1120 phytopathogenic <i>V. dahliae</i> isolates contained the <i>MAT1-1</i> idiomorph, whereas 99% contained <i>MAT1-2</i>. Nine unique multilocus microsatellite types comprised isolates of both mating types, eight of which were collected from the same substrate at the same time. Orthologs of 88 previously characterized sex-related genes from fungal model systems in the Ascoymycota were identified in the genome of <i>V</i>. <i>dahliae</i>, out of 93 genes investigated. Results of RT-PCR experiments using both mating types revealed that 10 arbitrarily chosen sex-related genes, including <i>MAT1-1-1</i> and <i>MAT1-2-1</i>, were constitutively expressed in <i>V</i>. <i>dahliae</i> cultures grown under laboratory conditions. Ratios of non-synonymous (amino-acid altering) to synonymous (silent) substitutions in <i>V</i>. <i>dahliae MAT1-1-1</i> and <i>MAT1-2-1</i> sequences were indistinguishable from the ratios observed in the <i>MAT</i> genes of sexual fungi in the <i>Pezizomycotina</i>. Patterns consistent with strong purifying selection were also observed in 18 other arbitrarily chosen <i>V</i>. <i>dahliae</i> sex-related genes, relative to the patterns in orthologs from fungi with known sexual stages. This study builds upon recent findings from other laboratories and mounts further evidence for an ancestral or cryptic sexual stage in <i>V. dahliae</i>.</p></div

Reverse-transcriptase PCR results of 10 <i>Verticillium dahliae</i> orthologs of genes associated with the sexual cycle in model fungal systems; gene names are provided for each lane; A) RT-PCR results from <i>V. dahliae</i> strain 58 (<i>MAT1-1)</i>.

<p>B) RT-PCR results from <i>V. dahliae</i> strain Ls 17 (<i>MAT1-2</i>);</p