Securing IoT Networks for Detection of Cyber Attacks using Automated Machine Learning

Cybercriminals are always developing innovative strategies to confound and frustrate their victims. Therefore, maintaining constant vigilance is essential if one wishes to protect the availability, confidentiality, and integrity of digital systems. Machine learning (ML) is becoming an increasingly powerful technique for doing intelligent cyber analysis, which enables proactive defenses. Machine learning (ML) has the potential to thwart future assaults by studying the recurring patterns that have already been successful. Nevertheless, there are two significant drawbacks associated with the utilization of ML in security analysis. To begin, the most advanced machine learning systems have significant problems with their computing overheads. Because of this constraint, firms are unable to completely embrace ML-based cyber strategies. Second, in order for security analysts to make advantage of ML for a wide variety of applications, they will need to develop specialized frameworks. In this study, we aim to put a numerical value on the degree to which a hub can improve the safety of an ecosystem. Typical cyberattacks were carried out on an Internet of Things (IoT) network located within a smart house in order to validate the hub. Further investigation of the intrusion detection system's (IDS) resistance to adversarial machine learning (AML) assaults was carried out. In this method, models can be attacked by supplying adversarial samples that attempt to take advantage of the defects in the detector that are present in the pre-trained model

De novo transcriptome analysis of rose-scented geranium provides insights into the metabolic specificity of terpene and tartaric acid biosynthesis

Abstract Background Rose-scented geranium ( Pelargonium sp.) is a perennial herb that produces a high value essential oil of fragrant significance due to the characteristic compositional blend of rose-oxide and acyclic monoterpenoids in foliage. Recently, the plant has also been shown to produce tartaric acid in leaf tissues. Rose-scented geranium represents top-tier cash crop in terms of economic returns and significance of the plant and plant products. However, there has hardly been any study on its metabolism and functional genomics, nor any genomic expression dataset resource is available in public domain. Therefore, to begin the gains in molecular understanding of specialized metabolic pathways of the plant, de novo sequencing of rose-scented geranium leaf transcriptome, transcript assembly, annotation, expression profiling as well as their validation were carried out. Results De novo transcriptome analysis resulted a total of 78,943 unique contigs (average length: 623\ua0bp, and N50 length: 752\ua0bp) from 15.44 million high quality raw reads. In silico functional annotation led to the identification of several putative genes representing terpene, ascorbic acid and tartaric acid biosynthetic pathways, hormone metabolism, and transcription factors. Additionally, a total of 6,040 simple sequence repeat (SSR) motifs were identified in 6.8% of the expressed transcripts. The highest frequency of SSR was of tri-nucleotides (50%). Further, transcriptome assembly was validated for randomly selected putative genes by standard PCR-based approach. In silico expression profile of assembled contigs were validated by real-time PCR analysis of selected transcripts. Conclusion Being the first report on transcriptome analysis of rose-scented geranium the data sets and the leads and directions reflected in this investigation will serve as a foundation for pursuing and understanding molecular aspects of its biology, and specialized metabolic pathways, metabolic engineering, genetic diversity as well as molecular breeding

Withanolide A is inherently de novo biosynthesized in roots of the medicinal plant Ashwagandha (Withania somnifera)

Ashwagandha (Withania somnifera Dunal., Solanaceae) is one of the most reputed medicinal plants of Ayurveda, the traditional medical system. Several of its traditionally proclaimed medicinal properties have been corroborated by recent molecular pharmacological investigations and have been shown to be associated with its specific secondary metabolites known as withanolides, the novel group of ergostane skeletal phytosteroids named after the plant. Withanolides are structurally distinct from tropane/nortropane alkaloids (usually found in Solanaceae plants) and are produced only by a few genera within Solanaceae. W. somnifera contains many structurally diverse withanolides in its leaves as well as roots. To date, there has been little biosynthetic or metabolism-related research on withanolides. It is thought that withanolides are synthesized in leaves and transported to roots like the tropane alkaloids, a group of bioactive secondary metabolites in Solanaceae members known to be synthesized in roots and transported to leaves for storage. To examine this, we have studied incorporation of 14C from [2-14C]-acetate and [U-14C]-glucose into withanolide A in the in vitro cultured normal roots as well as native/orphan roots of W. somnifera. Analysis of products by thin layer chromatography revealed that these primary metabolites were incorporated into withanolide A, demonstrating that root-contained withanolide A is de novo synthesized within roots from primary isoprenogenic precursors. Therefore, withanolides are synthesized in different parts of the plant (through operation of the complete metabolic pathway) rather than imported

RNAi and Homologous Over-Expression Based Functional Approaches Reveal Triterpenoid Synthase Gene-Cycloartenol Synthase Is Involved in Downstream Withanolide Biosynthesis in Withania somnifera.

Withania somnifera Dunal, is one of the most commonly used medicinal plant in Ayurvedic and indigenous medicine traditionally owing to its therapeutic potential, because of major chemical constituents, withanolides. Withanolide biosynthesis requires the activities of several enzymes in vivo. Cycloartenol synthase (CAS) is an important enzyme in the withanolide biosynthetic pathway, catalyzing cyclization of 2, 3 oxidosqualene into cycloartenol. In the present study, we have cloned full-length WsCAS from Withania somnifera by homology-based PCR method. For gene function investigation, we constructed three RNAi gene-silencing constructs in backbone of RNAi vector pGSA and a full-length over-expression construct. These constructs were transformed in Agrobacterium strain GV3101 for plant transformation in W. somnifera. Molecular and metabolite analysis was performed in putative Withania transformants. The PCR and Southern blot results showed the genomic integration of these RNAi and overexpression construct(s) in Withania genome. The qRT-PCR analysis showed that the expression of WsCAS gene was considerably downregulated in stable transgenic silenced Withania lines compared with the non-transformed control and HPLC analysis showed that withanolide content was greatly reduced in silenced lines. Transgenic plants over expressing CAS gene displayed enhanced level of CAS transcript and withanolide content compared to non-transformed controls. This work is the first full proof report of functional validation of any metabolic pathway gene in W. somnifera at whole plant level as per our knowledge and it will be further useful to understand the regulatory role of different genes involved in the biosynthesis of withanolides

Molecular Cloning and Biochemical Characterization of a Recombinant Sterol 3-O-Glucosyltransferase from Gymnema sylvestre R.Br. Catalyzing Biosynthesis of Steryl Glucosides

Gymnema sylvestre R.Br., a pharmacologically important herb vernacularly called Gur-Mar (sugar eliminator), is widely known for its antidiabetic action. This property of the herb has been attributed to the presence of bioactive triterpene glycosides. Although some information regarding pharmacology and phytochemical profiles of the plant are available, no attempts have been made so far to decipher the biosynthetic pathway and key enzymes involved in biosynthesis of steryl glucosides. The present report deals with the identification and catalytic characterization of a glucosyltransferase, catalyzing biosynthesis of steryl glycosides. The full length cDNA (2572 bp) contained an open reading frame of 2106 nucleotides that encoded a 701 amino acid protein, falling into GT-B subfamily of glycosyltransferases. The GsSGT was expressed in Escherichia coli and biochemical characterization of the recombinant enzyme suggested its key role in the biosynthesis of steryl glucosides with catalytic preference for C-3 hydroxyl group of sterols. To our knowledge, this pertains to be the first report on cloning and biochemical characterization of a sterol metabolism gene from G. sylvestre R.Br. catalyzing glucosylation of a variety of sterols of biological origin from diverse organisms such as bacteria, fungi, and plants

Biotransformation of banana pseudostem extract into a functional juice containing value added biomolecules of potential health benefits

453-462Banana is one of the most widely grown fruit crops, with the second largest produced fruit in the world. India is the largest producer of banana in the world. Banana cultivation generates huge residual biomass, which is generally wasted after harvesting of fruit. The present study represents a novel method for biotransformation of banana pseudostem extract into a functional juice, containing high value nondigestible oligosaccharides, and rare monosaccharide of nearly zero caloric value- D-allulose. The bioprocess involves employment of membrane separation techniques, and the biocatalysts executing glucosyltransferase and D-fructose epimerization activities. The bioprocessed banana pseudostem juice was estimated to contain prebiotic glucooligosaccharides (~5 g L-1) and D-allulose (~7 g L-1). Thus, the study represents a simple and innovative bioprocess for transformation of banana pseudostem extract into a functional juice possessing high value biomolecules that exert multifarious health benefits

Analysis of withanolides in root and leaf of Withania somnifera by HPLC with photodiode array and evaporative light scattering detection

A reversed-phase HPLC method for the simultaneous analysis of nine structurally similar withanolides, namely, 27-hydroxy withanone, 17-hydroxy withaferin A, 17-hydroxy-27-deoxy withaferin A, withaferin A, withanolide D, 27-hydroxy withanolide B, withanolide A, withanone and 27-deoxywithaferin A, has been developed using a linear binary gradient solvent system comprising methanol and water containing 0.1% acetic acid. Both photodiode array and evaporative light scattering detection were used to profile the extract compositions and to quantify the withanolides therein. Homogeneity and purity of each peak was ascertained by comparative evaluation of the on-line UV spectra of the eluted compounds with those of the reference compounds. The method has been validated with respect to various parameters of performance quality including computation regression analysis based on calibration curves, peak resolution factor, asymmetry factor, tailing factor, RSD (%) of retention time and peak area response, limit of quantivation, limit of detection, precision and recovery. The developed method has been applied to the analysis of leaf and root tissues of Withania somnifera for withanolide content