Detecting time-fragmented cache attacks against AES using Performance Monitoring Counters

Cache timing attacks use shared caches in multi-core processors as side channels to extract information from victim processes. These attacks are particularly dangerous in cloud infrastructures, in which the deployed countermeasures cause collateral effects in terms of performance loss and increase in energy consumption. We propose to monitor the victim process using an independent monitoring (detector) process, that continuously measures selected Performance Monitoring Counters (PMC) to detect the presence of an attack. Ad-hoc countermeasures can be applied only when such a risky situation arises. In our case, the victim process is the AES encryption algorithm and the attack is performed by means of random encryption requests. We demonstrate that PMCs are a feasible tool to detect the attack and that sampling PMCs at high frequencies is worse than sampling at lower frequencies in terms of detection capabilities, particularly when the attack is fragmented in time to try to be hidden from detection

Export, Assembly-line FDI or FDI with the Possibility of Technology Diffusion: Optimal Entry Mode for Multinationals

The paper tries to evaluate the optimal entry mode of a Multinational Company that is choosing among export, fragmented production structure with assembly-line FDI in LDC or complete production in LDC with FDI. The results show that if the plant installation cost is sufficiently high then the firm will find it profitable to export the finished product to the LDC market and the Government will not exercise any IPR restriction. If plant installation cost is below a certain critical level the MNC chooses complete LDC production with FDI over assembly-line FDI if the IPR restriction is strong, where the model assumes that a fake producer can copy the product if complete production takes place in LDC. In such a situation government will choose to protect IPR if government earning exceeds the cost of IPR protection, otherwise no monitoring is the optimal strategy of the government and MNC will choose the strategy of fragmented production structure and assembly-line FDI will take place in LDC.Export, Assembly-line FDI, FDI with Complete Production, IPR Protection

Monitoring distributed fragmented skylines

Distributed skyline computation is important for a wide range of domains, from distributed and web-based systems to ISP-network monitoring and distributed databases. The problem is particularly challenging in dynamic distributed settings, where the goal is to efficiently monitor a continuous skyline query over a collection of distributed streams. All existing work relies on the assumption of a single point of reference for object attributes/dimensions: objects may be vertically or horizontally partitioned, but the accurate value of each dimension for each object is always maintained by a single site. This assumption is unrealistic for several distributed applications, where object information is fragmented over a set of distributed streams (each monitored by a different site) and needs to be aggregated (e.g., averaged) across several sites. Furthermore, it is frequently useful to define skyline dimensions through complex functions over the aggregated objects, which raises further challenges for dealing with distribution and object fragmentation. We present the first known distributed algorithms for continuous monitoring of skylines over complex functions of fragmented multi-dimensional objects. Our algorithms rely on decomposition of the skyline monitoring problem to a select set of distributed threshold-crossing queries, which can be monitored locally at each site. We propose several optimizations, including: (a) a technique for adaptively determining the most efficient monitoring strategy for each object, (b) an approximate monitoring technique, and (c) a strategy that reduces communication overhead by grouping together threshold-crossing queries. Furthermore, we discuss how our proposed algorithms can be used to address other continuous query types. A thorough experimental study with synthetic and real-life data sets verifies the effectiveness of our schemes and demonstrates order-of-magnitude improvements in communication costs compared to the only alternative centralized solution

Degradation modeling applied to residual lifetime prediction using functional data analysis

Sensor-based degradation signals measure the accumulation of damage of an engineering system using sensor technology. Degradation signals can be used to estimate, for example, the distribution of the remaining life of partially degraded systems and/or their components. In this paper we present a nonparametric degradation modeling framework for making inference on the evolution of degradation signals that are observed sparsely or over short intervals of times. Furthermore, an empirical Bayes approach is used to update the stochastic parameters of the degradation model in real-time using training degradation signals for online monitoring of components operating in the field. The primary application of this Bayesian framework is updating the residual lifetime up to a degradation threshold of partially degraded components. We validate our degradation modeling approach using a real-world crack growth data set as well as a case study of simulated degradation signals.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS448 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Impacts of coffee fragmented landscapes on biodiversity and microclimate with emerging monitoring technologies

Habitat fragmentation and loss are causing biodiversity declines across the globe. As biodiversity is unevenly distributed, with many hotspots located in the tropics, conserving and protecting these areas is important to preserve as many species as possible. Chapter 2 presents an overview of the Ecology of the Atlantic Forest, a highly fragmented biodiversity hotspot. A major driver of habitat fragmentation is agriculture, and in the tropics coffee is major cash crop. Developing methods to monitor biodiversity effectively without labour intensive surveys can help us understand how communities are using fragmented landscapes and better inform management practices that promote biodiversity. Acoustic monitoring offers a promising set of tools to remotely monitor biodiversity. Developments in machine learning offer automatic species detection and classification in certain taxa. Chapters 3 and 4 use acoustic monitoring surveys conducted on fragmented landscapes in the Atlantic Forest to quantify bird and bat communities in forest and coffee matrix, respectively. Chapter 3 shows that acoustic composition can reflect local avian communities. Chapter 4 applies a convolutional neural network (CNN) optimised on UK bat calls to a Brazilian bat dataset to estimate bat diversity and show how bats preferentially use coffee habitats. In addition to monitoring biodiversity, monitoring microclimate forms a key part of climate smart agriculture for climate change mitigation. Coffee agriculture is limited to the tropics, overlapping with biodiverse regions, but is threatened by climate change. This presents a challenge to countries strongly reliant on coffee exports such as Brazil and Nicaragua. Chapter 5 uses data from microclimate weather stations in Nicaragua to demonstrate that sun-coffee management is vulnerable to supraoptimal temperature exposure regardless of local forest cover or elevation.Open Acces

Coordination of European Transnational Research in Organic Farming Systems

Organic agriculture and food markets have grown considerably, and organic agriculture addresses important challenges of European agriculture, such as the sustainable production of high-quality food, reducing dependency on high energy inputs, improving environmental and nature conservation, climate change adaptation, animal welfare and rural livelihoods. Organic farming and food systems still have a huge potential for innovation and improved solutions. Research activities will be important for this

Analysis of Toxic Amyloid Fibril Interactions at Natively Derived Membranes by Ellipsometry

There is an ongoing debate regarding the culprits of cytotoxicity associated with amyloid disorders. Although small pre-fibrillar amyloid oligomers have been implicated as the primary toxic species, the fibrillar amyloid material itself can also induce cytotoxicity. To investigate membrane disruption and cytotoxic effects associated with intact and fragmented fibrils, the novel in situ spectroscopic technique of Total Internal Reflection Ellipsometry (TIRE) was used. Fibril lipid interactions were monitored using natively derived whole cell membranes as a model of the in vivo environment. We show that fragmented fibrils have an increased ability to disrupt these natively derived membranes by causing a loss of material from the deposited surface when compared with unfragmented fibrils. This effect was corroborated by observations of membrane disruption in live cells, and by dye release assay using synthetic liposomes. Through these studies we demonstrate the use of TIRE for the analysis of protein-lipid interactions on natively derived lipid surfaces, and provide an explanation on how amyloid fibrils can cause a toxic gain of function, while entangled amyloid plaques exert minimal biological activity

An Architecture for Integrated Intelligence in Urban Management using Cloud Computing

With the emergence of new methodologies and technologies it has now become possible to manage large amounts of environmental sensing data and apply new integrated computing models to acquire information intelligence. This paper advocates the application of cloud capacity to support the information, communication and decision making needs of a wide variety of stakeholders in the complex business of the management of urban and regional development. The complexity lies in the interactions and impacts embodied in the concept of the urban-ecosystem at various governance levels. This highlights the need for more effective integrated environmental management systems. This paper offers a user-orientated approach based on requirements for an effective management of the urban-ecosystem and the potential contributions that can be supported by the cloud computing community. Furthermore, the commonality of the influence of the drivers of change at the urban level offers the opportunity for the cloud computing community to develop generic solutions that can serve the needs of hundreds of cities from Europe and indeed globally.Comment: 6 pages, 3 figure