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- Backes, John, et al.
(author)
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Reachability analysis for AWS-based networks
- 2019
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In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 11562 LNCS, s. 231-241
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Conference paper (peer-reviewed)abstract
- Cloud services provide the ability to provision virtual networked infrastructure on demand over the Internet. The rapid growth of these virtually provisioned cloud networks has increased the demand for automated reasoning tools capable of identifying misconfigurations or security vulnerabilities. This type of automation gives customers the assurance they need to deploy sensitive workloads. It can also reduce the cost and time-to-market for regulated customers looking to establish compliance certification for cloud-based applications. In this industrial case-study, we describe a new network reachability reasoning tool, called Tiros, that uses off-the-shelf automated theorem proving tools to fill this need. Tiros is the foundation of a recently introduced network security analysis feature in the Amazon Inspector service now available to millions of customers building applications in the cloud. Tiros is also used within Amazon Web Services (AWS) to automate the checking of compliance certification and adherence to security invariants for many AWS services that build on existing AWS networking features.
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2. |
- Zielinski, Brian L., et al.
(author)
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Patterns of Transcript Abundance of Eukaryotic Biogeochemically-Relevant Genes in the Amazon River Plume
- 2016
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In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:9
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Journal article (peer-reviewed)abstract
- The Amazon River has the largest discharge of all rivers on Earth, and its complex plume system fuels a wide array of biogeochemical processes, across a large area of the western tropical North Atlantic. The plume thus stimulates microbial processes affecting carbon sequestration and nutrient cycles at a global scale. Chromosomal gene expression patterns of the 2.0 to 156 mu m size-fraction eukaryotic microbial community were investigated in the Amazon River Plume, generating a robust dataset (more than 100 million mRNA sequences) that depicts the metabolic capabilities and interactions among the eukaryotic microbes. Combining classical oceanographic field measurements with metatranscriptomics yielded characterization of the hydrographic conditions simultaneous with a quantification of transcriptional activity and identity of the community. We highlight the patterns of eukaryotic gene expression for 31 biogeochemically significant gene targets hypothesized to be valuable within forecasting models. An advantage to this targeted approach is that the database of reference sequences used to identify the target genes was selectively constructed and highly curated optimizing taxonomic coverage, throughput, and the accuracy of annotations. A coastal diatom bloom highly expressed nitrate transporters and carbonic anhydrase presumably to support high growth rates and enhance uptake of low levels of dissolved nitrate and CO2. Diatom-diazotroph association (DDA: diatoms with nitrogen fixing symbionts) blooms were common when surface salinity was mesohaline and dissolved nitrate concentrations were below detection, and hence did not show evidence of nitrate utilization, suggesting they relied on ammonium transporters to aquire recently fixed nitrogen. These DDA blooms in the outer plume had rapid turnover of the photosystem D1 protein presumably caused by photodegradation under increased light penetration in clearer waters, and increased expression of silicon transporters as silicon became limiting. Expression of these genes, including carbonic anhydrase and transporters for nitrate and phosphate, were found to reflect the physiological status and biogeochemistry of river plume environments. These relatively stable patterns of eukaryotic transcript abundance occurred over modest spatiotemporal scales, with similarity observed in sample duplicates collected up to 2.45 km in space and 120 minutes in time. These results confirm the use of metatranscriptomics as a valuable tool to understand and predict microbial community function.
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