An Effective Conversation-Based Botnet Detection Method

A botnet is one of the most grievous threats to network security since it can evolve into many attacks, such as Denial-of-Service (DoS), spam, and phishing. However, current detection methods are inefficient to identify unknown botnet. The high-speed network environment makes botnet detection more difficult. To solve these problems, we improve the progress of packet processing technologies such as New Application Programming Interface (NAPI) and zero copy and propose an efficient quasi-real-time intrusion detection system. Our work detects botnet using supervised machine learning approach under the high-speed network environment. Our contributions are summarized as follows: (1) Build a detection framework using PF_RING for sniffing and processing network traces to extract flow features dynamically. (2) Use random forest model to extract promising conversation features. (3) Analyze the performance of different classification algorithms. The proposed method is demonstrated by well-known CTU13 dataset and nonmalicious applications. The experimental results show our conversation-based detection approach can identify botnet with higher accuracy and lower false positive rate than flow-based approach

Role of the Subtilisin-like Serine Protease CJPRB from <i>Cordyceps javanica</i> in Eliciting an Immune Response in <i>Hyphantria cunea</i>

Hyphantria cunea is a globally distributed quarantine plant pest. In a previous study, the Cordyceps javanica strain BE01 with a strong pathogenic effect on H. cunea was identified, and overexpression of the subtilisin-like serine protease CJPRB of this strain was found to accelerate the death of H. cunea (previous research results). In this study, the active recombinant CJPRB protein was obtained through the Pichia pastoris expression system. It was found that CJPRB protein administration to H. cunea via infectation, feeding and injection was able to induce changes in protective enzymes, including superoxide dismutase (SOD), peroxidase (POD), catalase (CAT) and polyphenol oxidase (PPO), and the expression of immune defense-related genes in H. cunea. In particular, CJPRB protein injection induced a more rapid, widespread and intense immune response in H. cunea compared to the other two treatment methods. The results suggest that the CJPRB protein may play a role in eliciting a host immune response during infectation by C. javanica

Selection of Reliable Reference Genes for RT-qPCR Analysis of Bursaphelenchus mucronatus Gene Expression From Different Habitats and Developmental Stages

Quantitative reverse transcription polymerase chain reaction (RT-qPCR), a sensitive technique for gene expression analysis, depends on the stability of the reference genes used for data normalization under different experimental conditions. Bursaphelenchus mucronatus, a pine-parasitic nematode varying in virulence, is widely distributed in natural pine forests throughout the northern hemisphere, but has not been investigated with respect to the identification of reference genes suitable for the normalization of RT-qPCR data. In the present study, eight candidate reference genes were analyzed in B. mucronatus under different habitat conditions and at different developmental stages. The expression stability of these genes was assessed by geNorm, NormFinder, BestKeeper, delta Cq, and RefFinder algorithms. In general, our results identified encoding beta-tubulin as the most stable gene. Moreover, pairwise analysis showed that three reference genes were sufficient to normalize the gene expression data under each set of conditions, with genes encoding beta-tubulin, 18S ribosomal RNA and ubiquitin-conjugating enzyme being the most suitable reference genes for different habitat conditions, whereas genes encoding beta-tubulin, histone, and 18S ribosomal RNA exhibited the most stable expression at different developmental stages. Validation of the selected reference genes was performed by profiling the expression of the fatty acid- and retinol-binding protein gene in different habitats, and by profiling the expression of the arginine kinase gene at different developmental stages. This first systematic analysis for the selection of suitable reference genes for RT-qPCR in B. mucronatus will facilitate future functional analyses and deep mining of genetic resources in this nematode

An alkaline protease from Bacillus cereus NJSZ-13 can act as a pathogenicity factor in infection of pinewood nematode

Abstract Endophytic bacteria are an important biological control for nematodes. We isolated the nematicidal Bacillus cereus NJSZ-13 from healthy Pinus elliottii trunks. Bioassay experiments showed killing of all tested nematodes by proteins from the NJSZ-13 culture filtrate within 72 h. Degradation of the nematode cuticles was observed, suggesting the action of extracellular bacterial enzymes. The responsible protease was purified by ammonium sulfate precipitation, hydrophobic interaction chromatography, ion-exchange chromatography, and SDS-PAGE. The protease had a molecular weight of 28 kDa and optimal activity at 55 °C and pH 9, indicating an alkaline protease. The study suggests the potential for using this B. cereus NJSZ-13 strain protease to prevent pinewood nematode infection

The Detection of Pine Wilt Disease: A Literature Review

Pine wilt disease (PWD) is a global quarantine disease of forests that mainly affects Pinaceae species. The disease spreads rapidly. Once infected, pine trees have an extremely high mortality rate. This paper provides a summary of the common techniques used to detect PWD, including morphological-, molecular-, chemical- and physical-based methods. By comprehending the complex relationship among pinewood nematodes, vectors and host pine trees and employing the available approaches for nematode detection, we can improve the implementation of intervention and control measures to effectively reduce the damage caused by PWD. Although conventional techniques allow a reliable diagnosis of the symptomatic phase, the volatile compound detection and remote sensing technology facilitate a rapid diagnosis during asymptomatic stages. Moreover, the remote sensing technology is capable of monitoring PWD over large areas. Therefore, multiple perspective evaluations based on these technologies are crucial for the rapid and effective detection of PWD

Promoting Effect of Choline-Phosphate Cytidylyltransferase Gene (<i>pcyt-1</i>) on Departure of Pinewood Nematode from <i>Monochamus alternatus</i>

In order to study the key gene in internal causes of pinewood nematode (PWN), Bursaphelenchus xylophilus, a departure from its vector beetle, Monochamus alternatus, we collected PWNs extracted from newly emerged M. alternatus and beetles 7 days after emergence. The total RNAs of the two groups of PWNs were extracted, transcriptomes sequencing was performed, and gene expression differences between the two groups of PWN were analyzed. It was found that the expression of the choline-phosphate cytidylyltransferase gene (pcyt-1) was markedly up-regulated. After inhibition of pcyt-1 expression by RNA interference, the rate of lipid degradation in PWN decreased significantly, and the motility of PWN also decreased significantly. The analysis identified that phosphatidylcholine could promote the emulsification and degradation of neutral lipid granules in PWN, which provides sufficient energy for PWN departure from M. alternatus. The up-regulation of the gene pcyt-1 is an important internal factor for PWN departure from its vector

CYP2A6, CYP1A1, and CYP2D6 polymorphisms in lung cancer patients from Central South China

Lung cancer is a common cause of cancer-related death. The link between risk of lung cancer susceptibility and genetic polymorphisms in metabolic enzymes is well documented. In this study, the relationships between lung cancer susceptibility and polymorphisms in the phase I metabolic enzyme genes CYP1A1, CYP2D6, and CYP2A6 were investigated. Genomic DNA was isolated from the peripheral blood of 201 healthy controls and 168 lung carcinoma patients from the Han ethnic group of Hunan Province in Central South China. Polymorphisms of the investigated genes were analyzed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and two-step allelic-specific PCR assays. No significant differences were found between the frequencies in cases and controls for the genotypes wild-type (WW), heterozygous mutant, or homozygous mutant; for CYP1A1 or CYP2D6; or for the genotypes WW, heterozygous deletion, or null genotype for CYP2A6. The three-locus model (CYP2A6/CYP1A1/CYP2D6) had a maximum test sample accuracy that was significant (P \u3c 0.001) with a cross-validation consistency of 10. These results indicated that the three-order interaction of CYP2A6, CYP1A1, and CYP2D6 polymorphisms might increase genetic susceptibility to lung cancer. We report the involvement of a three-order interaction between CYP1A1, CYP2A6, and CYP2D6 polymorphisms in lung cancer risk in people in Central South China, although no relationship between lung cancer risk and individual gene polymorphisms was found. © 2013 Springer Science+Business Media New York