Temporal and Spatial Analyses for Large-Scale Cyber Attacks

2012 ◽  
pp. 559-578 ◽  
Author(s):  
Haitao Du ◽  
Shanchieh Jay Yang
Keyword(s):  
Large Scale ◽  
Cyber Attacks ◽  
Spatial Analyses ◽  
Temporal And Spatial

scholarly journals Large-Scale Analysis of the Spatiotemporal Changes of Net Ecosystem Production in Hindu Kush Himalayan Region

2021 ◽  
Vol 13 (6) ◽  
pp. 1180
Author(s):  
Da Guo ◽  
Xiaoning Song ◽  
Ronghai Hu ◽  
Xinming Zhu ◽  
Yazhen Jiang ◽  
...  
Keyword(s):  
Large Scale ◽  
Net Primary Production ◽  
Carbon Sink ◽  
Carbon Sources ◽  
Spatial Dynamics ◽  
Tibet Plateau ◽  
Geostatistical Model ◽  
Hindu Kush ◽  
Temporal And Spatial ◽  
The Difference

The Hindu Kush Himalayan (HKH) region is one of the most ecologically vulnerable regions in the world. Several studies have been conducted on the dynamic changes of grassland in the HKH region, but few have considered grassland net ecosystem productivity (NEP). In this study, we quantitatively analyzed the temporal and spatial changes of NEP magnitude and the influence of climate factors on the HKH region from 2001 to 2018. The NEP magnitude was obtained by calculating the difference between the net primary production (NPP) estimated by the Carnegie–Ames Stanford Approach (CASA) model and the heterotrophic respiration (Rh) estimated by the geostatistical model. The results showed that the grassland ecosystem in the HKH region exhibited weak net carbon uptake with NEP values of 42.03 gC∙m−2∙yr−1, and the total net carbon sequestration was 0.077 Pg C. The distribution of NEP gradually increased from west to east, and in the Qinghai–Tibet Plateau, it gradually increased from northwest to southeast. The grassland carbon sources and sinks differed at different altitudes. The grassland was a carbon sink at 3000–5000 m, while grasslands below 3000 m and above 5000 m were carbon sources. Grassland NEP exhibited the strongest correlation with precipitation, and it had a lagging effect on precipitation. The correlation between NEP and the precipitation of the previous year was stronger than that of the current year. NEP was negatively correlated with temperature but not with solar radiation. The study of the temporal and spatial dynamics of NEP in the HKH region can provide a theoretical basis to help herders balance grazing and forage.

scholarly journals A Potential of microRNAs for High-Content Screening

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Andrius Serva ◽  
Christoph Claas ◽  
Vytaute Starkuviene
Keyword(s):  
Large Scale ◽  
Cellular Processes ◽  
Comprehensive Knowledge ◽  
Functional Models ◽  
Rapid Accumulation ◽  
Health And Disease ◽  
Temporal And Spatial ◽  
And Function ◽  
Functional Analyses ◽  
Immense Potential

In the last years miRNAs have increasingly been recognised as potent posttranscriptional regulators of gene expression. Possibly, miRNAs exert their action on virtually any biological process by simultaneous regulation of numerous genes. The importance of miRNA-based regulation in health and disease has inspired research to investigate diverse aspects of miRNA origin, biogenesis, and function. Despite the recent rapid accumulation of experimental data, and the emergence of functional models, the complexity of miRNA-based regulation is still far from being well understood. In particular, we lack comprehensive knowledge as to which cellular processes are regulated by which miRNAs, and, furthermore, how temporal and spatial interactions of miRNAs to their targets occur. Results from large-scale functional analyses have immense potential to address these questions. In this review, we discuss the latest progress in application of high-content and high-throughput functional analysis for the systematic elucidation of the biological roles of miRNAs.

scholarly journals Influence of Stratospheric Sudden Warming on AIRS Midtropospheric CO2

2013 ◽  
Vol 70 (8) ◽  
pp. 2566-2573 ◽  
Author(s):  
Xun Jiang ◽  
Jingqian Wang ◽  
Edward T. Olsen ◽  
Thomas Pagano ◽  
Luke L. Chen ◽  
...  
Keyword(s):  
Large Scale ◽  
Principal Component ◽  
Department Of Energy ◽  
Atmospheric Infrared Sounder ◽  
Stratospheric Sudden Warming ◽  
Chemical Tracers ◽  
Before And After ◽  
Temporal And Spatial ◽  
Global Reanalysis ◽  
Height Data

Abstract Midtropospheric CO2 retrievals from the Atmospheric Infrared Sounder (AIRS) were used to explore the influence of stratospheric sudden warming (SSW) on CO2 in the middle to upper troposphere. To choose the SSW events that had strong coupling between the stratosphere and troposphere, the authors applied a principal component analysis to the NCEP/Department of Energy Global Reanalysis 2 (NCEP-2) geopotential height data at 17 pressure levels. Two events (April 2003 and March 2005) that have strong couplings between the stratosphere and troposphere were chosen to investigate the influence of SSW on AIRS midtropospheric CO2. The authors investigated the temporal and spatial variations of AIRS midtropospheric CO2 before and after the SSW events and found that the midtropospheric CO2 concentrations increased by 2–3 ppm within a few days after the SSW events. These results can be used to better understand how the chemical tracers respond to the large-scale dynamics in the high latitudes.

scholarly journals Landforms and rural development: The evolution of human settlements at alpine alluvial fans in the Admont Valley, Austria, since 1784 AD

2019 ◽  
Vol 21 (1) ◽  
pp. 29-43
Author(s):  
Andreas KELLERER-PIRKLBAUER ◽  
Julia EULENSTEIN
Keyword(s):  
Eastern Europe ◽  
Large Scale ◽  
Central And Eastern Europe ◽  
Alluvial Fans ◽  
Spatial Analyses ◽  
Hazard Zonation ◽  
Risk Zones ◽  
Zonation Maps ◽  
Francis I ◽  
Insight Into

We used two historical maps that cover vast areas of central and eastern Europe at rather large scale dating to 1784 (First Military Survey of the Habsburg Empire; total extent 640,000 km²; scale 1: 28,800) and 1824 (cadastral land register of Francis I; 670,000 km²; 1: 2,880) to extracted individual buildings located at several alluvial fans in one valley in Austria (Admont Valley). Historic buildings were mapped and compared with present building (airborne–laserscanning based; 2008–2017), geomorphic (landform distribution), geomorphodynamic (documented damaging events at torrents), and spatial planning (hazard zonation maps) data. Results show that 69.2% of all present buildings are located at only 7% of the study area. Whereas the 1784–data are too inaccurate and unprecise for detailed spatial analyses, the 1824–data are very accurate and precise allowing spatial and socio–economic insight into the population and building evolution over a 190–year period. Results show for instance that despite a tremendous increase in buildings (911 in 1824; 3554 in 2008–2017), the proportion of buildings exposed to torrents–related natural hazards significantly decreased by 10.4% for yellow (moderate–risk) and by 13.7% for red (high–risk) zones. Similar historio–geomorphological studies as presented here might be accomplished in other countries in central and eastern Europe covered by the indicated historical map products.

scholarly journals Temporal and spatial distributions of precipitation on the Huang-Huai-Hai Plain during 1960–2019, China

2021 ◽  
Author(s):  
Minhua Ling ◽  
Hongbao Han ◽  
Xingling Wei ◽  
Cuimei Lv
Keyword(s):  
Spatial Distribution ◽  
Large Scale ◽  
Kendall Test ◽  
Winter Precipitation ◽  
Annual Precipitation ◽  
Temporal And Spatial Distribution ◽  
Global Pattern ◽  
The North ◽  
Variance Contribution ◽  
Temporal And Spatial

Abstract The Huang-Huai-Hai Plain is an important commercial grain production base in China. Understanding the temporal and spatial variations in precipitation can help prevent drought and flood disasters and ensure food security. Based on the precipitation data for the Huang-Huai-Hai Plain from 1960 to 2019, this study analysed the spatiotemporal distribution of total precipitation at different time scales using the Mann–Kendall test, the wavelet analysis, the empirical orthogonal function (EOF), and the centre-of-gravity model. The results were as follows: (1) The winter precipitation showed a significant upward trend on the Huang-Huai-Hai Plain, while other seasonal trends were not significant. (2) The precipitation on the Huang-Huai-Hai Plain shows a zonal decreasing distribution from southeast to northwest. (3) The application of the EOF method revealed the temporal and spatial distribution characteristics of the precipitation field. The cumulative variance contribution rate of the first two eigenvectors reached 51.5%, revealing two typical distribution fields, namely a ‘global pattern’ and a ‘north-south pattern’. The ‘global pattern’ is the decisive mode, indicating that precipitation on the Huang-Huai-Hai Plain is affected by large-scale weather systems. (4) The annual precipitation barycentres on the Huang-Huai-Hai Plain were located in Jining city and Taian city, Shandong Province, and the spatial distribution pattern was north-south. The annual precipitation barycentres tended to move southwest, but the trend was not obvious. The annual precipitation barycentre is expected to continue to shift to the north in 2020.

scholarly journals Enhanced Security In Cloud With Multi-Level Intrusion Detection System

2015 ◽  
pp. 9-12
Author(s):  
M. KUZHALISAI ◽  
G. GAYATHRI
Keyword(s):  
Cloud Computing ◽  
Intrusion Detection ◽  
Large Scale ◽  
Detection System ◽  
Computing System ◽  
Cyber Attacks ◽  
Security Level ◽  
Security Service ◽  
Cloud Computing System ◽  
System Resource

Cloud computing is a new type of service which provides large scale computing resource to each customer. Cloud Computing Systems can be easily threatened by various cyber attacks, because most of Cloud computing system needs to contain some Intrusion Detection Systems (IDS) for protecting each Virtual Machine (VM) against threats. In this case, there exists a tradeoff between the security level of the IDS and the system performance. If the IDS provide stronger security service using more rules or patterns, then it needs much more computing resources in proportion to the strength of security. So the amount of resources allocating for customers decreases. Another problem in Cloud Computing is that, huge amount of logs makes system administrators hard to analyse them. In this paper, we propose a method that enables cloud computing system to achieve both effectiveness of using the system resource and strength of the security service without trade-off between them.

An Overview of Electronic Attacks

2011 ◽  
pp. 1-26 ◽  
Author(s):  
Thomas M. Chen ◽  
Chris Davis
Keyword(s):  
Large Scale ◽  
Cyber Attacks ◽  
Foreseeable Future ◽  
Comprehensive Understanding ◽  
Digital Crime ◽  
Crime Investigation ◽  
Cover Up

This chapter gives an overview of the major types of electronic attacks encountered today and likely to continue into the foreseeable future. A comprehensive understanding of attackers, their motives, and their methods is a prerequisite for digital crime investigation. The range of possible cyber attacks is almost unlimited, but many attacks generally follow the basic steps of reconnaissance, gaining access, and cover-up. We highlight common methods and tools used by attackers in each step. In addition, attacks are not necessarily directed toward specific targets. Viruses, worms, and spam are examples of large-scale attacks directed at compromising as many systems as possible.

scholarly journals Comparative Study between Big Data Analysis Techniques in Intrusion Detection

2018 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
Mounir Hafsa ◽  
Farah Jemili
Keyword(s):  
Intrusion Detection ◽  
Real Time ◽  
Large Scale ◽  
Fault Tolerant ◽  
Time Frame ◽  
Cyber Attacks ◽  
Sensitive Information ◽  
Cyber Attack ◽  
Processing Power ◽  
Damage Costs

Cybersecurity ventures expect that cyber-attack damage costs will rise to $11.5 billion in 2019 and that a business will fall victim to a cyber-attack every 14 seconds. Notice here that the time frame for such an event is seconds. With petabytes of data generated each day, this is a challenging task for traditional intrusion detection systems (IDSs). Protecting sensitive information is a major concern for both businesses and governments. Therefore, the need for a real-time, large-scale and effective IDS is a must. In this work, we present a cloud-based, fault tolerant, scalable and distributed IDS that uses Apache Spark Structured Streaming and its Machine Learning library (MLlib) to detect intrusions in real-time. To demonstrate the efficacy and effectivity of this system, we implement the proposed system within Microsoft Azure Cloud, as it provides both processing power and storage capabilities. A decision tree algorithm is used to predict the nature of incoming data. For this task, the use of the MAWILab dataset as a data source will give better insights about the system capabilities against cyber-attacks. The experimental results showed a 99.95% accuracy and more than 55,175 events per second were processed by the proposed system on a small cluster.

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