On the Significance of Process Comprehension for Conducting Targeted ICS Attacks

The exploitation of Industrial Control Systems (ICSs) has been described as both easy and impossible, where is the truth? Post-Stuxnet works have included a plethora of ICS focused cyber secu- rity research activities, with topics covering device maturity, network protocols, and overall cyber security culture. We often hear the notion of ICSs being highly vulnerable due to a lack of inbuilt security mechanisms, considered a low hanging fruit to a variety of low skilled threat actors. While there is substantial evidence to support such a notion, when considering targeted attacks on ICS, it is hard to believe an attacker with limited resources, such as a script kiddie or hacktivist, using publicly accessible tools and exploits alone, would have adequate knowledge and resources to achieve targeted operational process manipulation, while simultaneously evade detection. Through use of a testbed environment, this paper provides two practical examples based on a Man-In-The-Middle scenario, demonstrating the types of information an attacker would need obtain, collate, and comprehend, in order to begin targeted process manipulation and detection avoidance. This allows for a clearer view of associated challenges, and illustrate why targeted ICS exploitation might not be possible for every malicious actor

Investigation of the <i>Fusarium virguliforme</i> Transcriptomes Induced during Infection of Soybean Roots Suggests that Enzymes with Hydrolytic Activities Could Play a Major Role in Root Necrosis

<div><p>Sudden death syndrome (SDS) is caused by the fungal pathogen, <i>Fusarium virguliforme</i>, and is a major threat to soybean production in North America. There are two major components of this disease: (i) root necrosis and (ii) foliar SDS. Root symptoms consist of root necrosis with vascular discoloration. Foliar SDS is characterized by interveinal chlorosis and leaf necrosis, and in severe cases by flower and pod abscission. A major toxin involved in initiating foliar SDS has been identified. Nothing is known about how root necrosis develops. In order to unravel the mechanisms used by the pathogen to cause root necrosis, the transcriptome of the pathogen in infected soybean root tissues of a susceptible cultivar, ‘Essex’, was investigated. The transcriptomes of the germinating conidia and mycelia were also examined. Of the 14,845 predicted <i>F</i>. <i>virguliforme</i> genes, we observed that 12,017 (81%) were expressed in germinating conidia and 12,208 (82%) in mycelia and 10,626 (72%) in infected soybean roots. Of the 10,626 genes induced in infected roots, 224 were transcribed only following infection. Expression of several infection-induced genes encoding enzymes with oxidation-reduction properties suggests that degradation of antimicrobial compounds such as the phytoalexin, glyceollin, could be important in early stages of the root tissue infection. Enzymes with hydrolytic and catalytic activities could play an important role in establishing the necrotrophic phase. The expression of a large number of genes encoding enzymes with catalytic and hydrolytic activities during the late infection stages suggests that cell wall degradation could be involved in root necrosis and the establishment of the necrotrophic phase in this pathogen.</p></div

Quantitative RT-PCR of a few selected genes, evaluated in RT-PCR analyses.

<p>Quantitative RT-PCR (qRT-PCR) was performed for a few selected virulence genes using gene specific primers to validate semi-quantitative RT-PCR data. (A) <i>g10929</i>, (B) <i>g13754</i>, (C) <i>g11449</i>, (D) <i>g8479</i>, (E) <i>g8640</i>, (F) <i>g12211</i>, (G) <i>g6063</i> and (H) <i>g8642</i>. The <i>Fusarium GAPDH</i> gene was used as an internal control. Relative gene expression levels were determined in proportions to levels of corresponding levels of 1 d <i>F</i>. <i>virguliforme-</i>infected samples, which are defined as 1. Error bars represent standard deviation (SD) of two independent biological replicates (n = 6).</p

Differentially induced <i>F</i>. <i>virguliforme</i> genes that are predicted to encode secretory proteins during early and late infection stages.

<p>Differentially induced <i>F</i>. <i>virguliforme</i> genes that are predicted to encode secretory proteins during early and late infection stages.</p

<i>F</i>. <i>virguliforme</i> genes expressed in germinating conidia, mycelia and infected soybean root tissues.

<p><i>F</i>. <i>virguliforme</i> genes expressed in germinating conidia, mycelia and infected soybean root tissues.</p

Categories of <i>F</i>. <i>virguliforme</i> genes based on BLAST2GO analyses for biological processes.

<p>A, Categories of <i>F</i>. <i>virguliforme</i> genes with 10-fold induction. B, Categories of <i>F</i>. <i>virguliforme</i> genes with 50-fold induction. C, Percentage of genes distributed under different functional categories for biological process are presented as bar diagram for <i>F</i>. <i>virguliforme</i> genes with 10 and 50 fold induction over mycelia and germinating conidia.</p

Transcript profiles of the <i>F</i>. <i>virguliforme</i> genes in various tissues.

<p>(A). Percentage sequence reads of <i>F</i>. <i>virguliforme</i> and soybean genes during infection. (B). Sequence reads of <i>F</i>. <i>virguliforme</i> genes among various tissue samples. (C). Venn diagram showing unique and common <i>F</i>. <i>virguliforme</i> genes among germinating spore, mycelia and infected soybean roots. S, genes expressed only in germinating conidia; M, genes expressed only in mycelia; I, genes expressed in infected roots; SM, genes expressed in both spores and mycelia; SI, genes expressed in both spores and infected roots; MI, genes expressed in mycelia and infected roots; SMI, genes expressed in spores, mycelia and infected roots. The genes with a minimum of three reads were considered in developing the Venn diagram. The 984 genes having sequence reads below three were not considered for the Venn diagram.</p

Categories of <i>F</i>. <i>virguliforme</i> genes based on BLAST2GO analyses for molecular functions.

<p>A, Categories of <i>F</i>. <i>virguliforme</i> genes with 10-fold induction. B, Categories of <i>F</i>. <i>virguliforme</i> genes with 50-fold induction. C, Percentage of genes distributed under different functional categories for molecular functions are presented as bar diagram for <i>F</i>. <i>virguliforme</i> genes with 10 and 50 fold induction over mycelia and germinating conidia.</p

Up or down regulated <i>F</i>. <i>virguliforme</i> genes during infection compared to germinating conidia and mycelia.

<p>Up or down regulated <i>F</i>. <i>virguliforme</i> genes during infection compared to germinating conidia and mycelia.</p

Flow diagram of the steps followed in conducting the transcriptomic analysis.

<p>(i) RNA samples were isolated from germinating spore, mycelia, early stage of infection and late stage of infection (details in materials and methods). (ii) RNA samples were reverse transcribed into cDNA and sequenced using Solexa sequencing platform. (iii) Assembling of the RNA sequence datasets and mapping to reference sequence (<a href="http://fvgbrowse.agron.iastate.edu/" target="_blank">http://fvgbrowse.agron.iastate.edu/</a>) was conducted using Bowtie. (iv) Determined the expression levels of individual genes (RPKM values). (v) Validation of the RNA sequence data by PCR analyses (iv) Conducted functional categorization of <i>F</i>. <i>virguliforme</i> genes by BLAST2GO analyses and validated expression levels of a few selected genes from different functional categories. (v) Identification of putative <i>F</i>. <i>virguliforme</i> virulence genes. dpi, day post inoculation.</p