• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2781-2800
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• 2016

Emerging attacks aim to access proprietary assets and steal data for business or political motives, such as Operation Aurora and Operation Shady RAT. Skilled Intruders would likely remove their traces on targeted hosts, but their network movements, which are continuously recorded by network devices, cannot be easily eliminated by themselves. However, without complete knowledge about both inbound/outbound and internal traffic, it is difficult for security team to unveil hidden traces of intruders. In this paper, we propose an autonomous anomaly detection system based on behavior profiling and relation mining. The single-hop access profiling model employ a novel linear grouping algorithm PSOLGA to create behavior profiles for each individual server application discovered automatically in historical flow analysis. Besides that, the double-hop access relation model utilizes in-memory graph to mine time-sequenced access relations between different server applications. Using the behavior profiles and relation rules, this approach is able to detect possible anomalies and violations in real-time detection. Finally, the experimental results demonstrate that the designed models are promising in terms of accuracy and computational efficiency.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.10
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• pp.1456-1463
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• 2017

Objective: To investigate the effect of host genetics on gut microbial diversity, we performed a structural survey of the fecal microbiota of four purebred boar pig lines: Duroc, Landrace, Hampshire, and Yorkshire. Methods: The V3-V4 regions of the 16S rRNA genes were amplified and sequenced. Results: A total of 783 operational taxonomic units were shared by all breeds, whereas others were breed-specific. Firmicutes and Bacteroidetes dominated the majority of the fecal microbiota; Clostridia, Bacilli, and Bacteroidia were the major classes. Nine predominant genera were observed in all breeds and eight of them can produce short-chain fatty acids. Some bacteria can secrete cellulase to aid fiber digestion by the host. Butyric, isobutyric, valeric, and isovaleric acid levels were highest in Landrace pigs, whereas acetic and propionic acid were highest in the Hampshire breed. Heatmap was used to revealed breed-specific bacteria. Principal coordinate analysis of fecal bacteria revealed that the Landrace and Yorkshire breeds had high similarity and were clearly separated from the Duroc and Hampshire breeds. Conclusion: Overall, this study is the first time to compare the fecal microbiomes of four breeds of boar pig by high-throughput sequencing and to use Spearman's rank correlation to analyze competition and cooperation among the core bacteria.

• Journal of Veterinary Science
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• v.21 no.4
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• pp.65.1-65.13
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• 2020

Background: Aleutian mink disease virus (AMDV) causes major economic losses in fur-bearing animal production. The control of most AMDV outbreaks is complex due to the difficulties of establishing the source of infection based only on the available on-farm epidemiological data. In this sense, phylogenetic analysis of the strains present in a farm may help elucidate the origin of the infection and improve the control and biosecurity measures. Objectives: This study had the following aims: characterize the AMDV strains from most outbreaks produced at Spanish farms between 2012-2019 at the molecular level, and assess the utility of the combined use of molecular and epidemiological data to track the possible routes of infection. Methods: Thirty-seven strains from 17 farms were partially sequenced for the NS1 and VP2 genes and analyzed phylogenetically with other strains described worldwide. Results: Spanish AMDV strains are clustered in four major clades that generally show a good geographical correlation, confirming that most had been established in Spain a long time ago. The combined study of phylogenetic results and epidemiological information of each farm suggests that most of the AMDV outbreaks since 2012 had been produced by within-farm reservoirs, while a few of them may have been due to the introduction of the virus through international trade. Conclusions: The combination of phylogenetic inference, together with epidemiological data, helps assess the possible origin of AMDV infections in mink farms and improving the control and prevention of this disease.

• Journal of the Korean Geographical Society
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• v.40 no.2 s.107
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• pp.221-241
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• 2005

Land Use and Land Cover Changes (LUCC) occur over a wide range of space and time scales, and involve complex natural, socio-economic, and institutional processes. Therefore, modelling and predicting LUCC demands an understanding of how various measured properties behave when considered at different scales. Understanding spatial and temporal variability of driving forces and constraints on LUCC is central to understanding the scaling issues. This paper aims to 1) assess the heterogeneity of land cover change processes over the landscape in northern Ghana, where intensification of agricultural activities has been the dominant land cover change process during the past 15 years, 2) characterise dominant land cover change mechanisms for various spatial scales, and 3) identify the optimal spatial scale for LUCC modelling in a savanna landscape. A multivariate statistical method was first applied to identify land cover change intensity (LCCI), using four time-sequenced NDVI images derived from LANDSAT scenes. Three proxy land use change predictors: distance from roads, distance from surface water bodies, and a terrain characterisation index, were regressed against the LCCI using a multi-scale hierarchical adaptive model to identify scale dependency and spatial heterogeneity of LUCC processes. High spatial associations between the LCCI and land use change predictors were mostly limited to moving windows smaller than 10$\times$10km. With increasing window size, LUCC processes within the window tend to be too diverse to establish clear trends, because changes in one part of the window are compensated elsewhere. This results in a reduced correlation between LCCI and land use change predictors at a coarser spatial extent. The spatial coverage of 5-l0km is incidentally equivalent to a village or community area in the study region. In order to reduce spatial variability of land use change processes for regional or national level LUCC modelling, we suggest that the village level is the optimal spatial investigation unit in this savanna landscape.