Comparison of ITS and IGS1 regions for strain typing of clinical and non-clinical isolates of Pichia anomala

Pichia anomala is an emerging nosocomial pathogen and there is a need for methods that distinguish between different P. anomala strains. In the typing of several clinical as well as non-clinical P. anomala strains, the sequence variation of the internal transcribed spacer (ITS) was found to be inadequate for typing purposes. The intergenic spacer 1 (IGS1) region of the rDNA of several P. anomala strains was therefore investigated in detail. The IGS1 region (which varied from 1213 to 1231 bp in length) was interspersed with repeats and had more variation than the ITS regions. Comparative analysis in cases where analysis by the ITS was ambiguous clearly revealed the IGS1 region to be a more discriminatory tool in the typing of P. anomala strains

Filtering Security Alerts for the Analysis of a Production SaaS Cloud

Security alerts collected under real workload conditions represent a goldmine of information to protect integrity and confidentiality of a production Cloud. Nevertheless, the volume of runtime alerts overwhelms operations teams and makes forensics hard and time consuming. This paper investigates the use of different text weighting schemes to filter an average volume of 1,000 alerts/day produced by a security information and event management (SIEM) tool in a production SaaS Cloud. As a result, a filtering approach based on the log.entropy scheme, has been developed to pinpoint relevant information across the amount of daily textual alerts. The proposed filter is valuable to support operations team and allowed identifying real incidents that affected several nodes and required manual response