978 resultados para Key-recovery attack


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This paper addresses the security of a specific class of common watermarking methods based on Dither modulation-quantisation index modulation (DM-QIM) and focusing on watermark-only attacks (WOA). The vulnerabilities of and probable attacks on lattice structure based watermark embedding methods have been presented in the literature. DM-QIM is one of the best known lattice structure based watermarking techniques. In this paper, the authors discuss a watermark-only attack scenario (the attacker has access to a single watermarked content only). In the literature it is an assumption that DM-QIM methods are secure to WOA. However, the authors show that the DM-QIM based embedding method is vulnerable against a guided key guessing attack by exploiting subtle statistical regularities in the feature space embeddings for time series and images. Using a distribution-free algorithm, this paper presents an analysis of the attack and numerical results for multiple examples of image and time series data.

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This paper addresses the security of a specific class of common watermarking methods based on Dither modulation-quantisation index modulation (DM-QIM) and focusing on watermark-only attacks (WOA). The vulnerabilities of and probable attacks on lattice structure based watermark embedding methods have been presented in the literature. DM-QIM is one of the best known lattice structure based watermarking techniques. In this paper, the authors discuss a watermark-only attack scenario (the attacker has access to a single watermarked content only). In the literature it is an assumption that DM-QIM methods are secure to WOA. However, the authors show that the DM-QIM based embedding method is vulnerable against a guided key guessing attack by exploiting subtle statistical regularities in the feature space embeddings for time series and images. Using a distribution-free algorithm, this paper presents an analysis of the attack and numerical results for multiple examples of image and time series data.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Reticulados têm sido aplicados de diferentes maneiras em criptografia. Inicialmente utilizados para a destruição de criptossistemas, eles foram posteriormente aplicados na construção de novos esquemas, incluindo criptossistemas assimétricos, esquemas de assinatura cega e os primeiros métodos para encriptação completamente homomórfica. Contudo, seu desempenho ainda é proibitivamente lenta em muitos casos. Neste trabalho, expandimos técnicas originalmente desenvolvidas para encriptação homomórfica, tornando-as mais genéricas e aplicando-as no esquema GGH-YK-M, um esquema de encriptação de chave pública, e no esquema LMSV, a única construção homomórfica que não sucumbiu a ataques de recuperação de chaves IND-CCA1 até o momento. Em nossos testes, reduzimos o tamanho das chaves do GGH-YK-M em uma ordem de complexidade, especificamente, de O(n2 lg n) para O(n lg n), onde n é um parâmetro público do esquema. A nova técnica também atinge processamento mais rápido em todas as operações envolvidas em um criptossistema assimétrico, isto é, geração de chaves, encriptação e decriptação. A melhora mais significativa é na geração de chaves, que se torna mais de 3 ordens de magnitude mais rápida que resultados anteriores, enquanto a encriptação se torna por volta de 2 ordens de magnitude mais rápida. Para decriptação, nossa implementação é dez vezes mais rápida que a literatura. Também mostramos que é possível aumentar a segurança do esquema LMSV contra os ataques quânticos de recuperação de chaves recentemente publicados pela agência britânica GCHQ. Isso é feito através da adoção de reticulados não-ciclotômicos baseados em anéis polinomiais irredutíveis quase-circulantes. Em nossa implementação, o desempenho da encriptação é virtualmente idêntico, e a decriptação torna-se ligeiramente inferior, um pequeno preço a se pagar pelo aumento de segurança. A geração de chaves, porém, é muito mais lenta, devido à necessidade de se utilizar um método mais genérico e caro. A existência de métodos dedicados altamente eficientes para a geração de chaves nesta variante mais segura do LMSV permanece como um problema em aberto.

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Recent advances in electronic and computer technologies lead to wide-spread deployment of wireless sensor networks (WSNs). WSNs have wide range applications, including military sensing and tracking, environment monitoring, smart environments, etc. Many WSNs have mission-critical tasks, such as military applications. Thus, the security issues in WSNs are kept in the foreground among research areas. Compared with other wireless networks, such as ad hoc, and cellular networks, security in WSNs is more complicated due to the constrained capabilities of sensor nodes and the properties of the deployment, such as large scale, hostile environment, etc. Security issues mainly come from attacks. In general, the attacks in WSNs can be classified as external attacks and internal attacks. In an external attack, the attacking node is not an authorized participant of the sensor network. Cryptography and other security methods can prevent some of external attacks. However, node compromise, the major and unique problem that leads to internal attacks, will eliminate all the efforts to prevent attacks. Knowing the probability of node compromise will help systems to detect and defend against it. Although there are some approaches that can be used to detect and defend against node compromise, few of them have the ability to estimate the probability of node compromise. Hence, we develop basic uniform, basic gradient, intelligent uniform and intelligent gradient models for node compromise distribution in order to adapt to different application environments by using probability theory. These models allow systems to estimate the probability of node compromise. Applying these models in system security designs can improve system security and decrease the overheads nearly in every security area. Moreover, based on these models, we design a novel secure routing algorithm to defend against the routing security issue that comes from the nodes that have already been compromised but have not been detected by the node compromise detecting mechanism. The routing paths in our algorithm detour those nodes which have already been detected as compromised nodes or have larger probabilities of being compromised. Simulation results show that our algorithm is effective to protect routing paths from node compromise whether detected or not.

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Increasing the size of training data in many computer vision tasks has shown to be very effective. Using large scale image datasets (e.g. ImageNet) with simple learning techniques (e.g. linear classifiers) one can achieve state-of-the-art performance in object recognition compared to sophisticated learning techniques on smaller image sets. Semantic search on visual data has become very popular. There are billions of images on the internet and the number is increasing every day. Dealing with large scale image sets is intense per se. They take a significant amount of memory that makes it impossible to process the images with complex algorithms on single CPU machines. Finding an efficient image representation can be a key to attack this problem. A representation being efficient is not enough for image understanding. It should be comprehensive and rich in carrying semantic information. In this proposal we develop an approach to computing binary codes that provide a rich and efficient image representation. We demonstrate several tasks in which binary features can be very effective. We show how binary features can speed up large scale image classification. We present learning techniques to learn the binary features from supervised image set (With different types of semantic supervision; class labels, textual descriptions). We propose several problems that are very important in finding and using efficient image representation.

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CONTEXT Enhanced Recovery after Surgery (ERAS) programs are multimodal care pathways that aim to decrease intra-operative blood loss, decrease postoperative complications, and reduce recovery times. OBJECTIVE To overview the use and key elements of ERAS pathways, and define needs for future clinical trials. EVIDENCE ACQUISITION A comprehensive systematic MEDLINE search was performed for English language reports published before May 2015 using the terms "postoperative period," "postoperative care," "enhanced recovery after surgery," "enhanced recovery," "accelerated recovery," "fast track recovery," "recovery program," "recovery pathway", "ERAS," and "urology" or "cystectomy" or "urologic surgery." EVIDENCE SYNTHESIS We identified 18 eligible articles. Patient counseling, physical conditioning, avoiding excessive alcohol and smoking, and good nutrition appeared to protect against postoperative complications. Fasting from solid food for only 6h and perioperative liquid-carbohydrate loading up to 2h prior to surgery appeared to be safe and reduced recovery times. Restricted, balanced, and goal-directed fluid replacement is effective when individualized, depending on patient morbidity and surgical procedure. Decreased intraoperative blood loss may be achieved by several measures. Deep vein thrombosis prophylaxis, antibiotic prophylaxis, and thermoregulation were found to help reduce postsurgical complications, as was a multimodal approach to postoperative nausea, vomiting, and analgesia. Chewing gum, prokinetic agents, oral laxatives, and an early resumption to normal diet appear to aid faster return to normal bowel function. Further studies should compare anesthetic protocols, refine analgesia, and evaluate the importance of robot-assisted surgery and the need/timing for drains and catheters. CONCLUSIONS ERAS regimens are multidisciplinary, multimodal pathways that optimize postoperative recovery. PATIENT SUMMARY This review provides an overview of the use and key elements of Enhanced Recovery after Surgery programs, which are multimodal, multidisciplinary care pathways that aim to optimize postoperative recovery. Additional conclusions include identifying effective procedures within Enhanced Recovery after Surgery programs and defining needs for future clinical trials.

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With the advent of cloud computing, many applications have embraced the ensuing paradigm shift towards modern distributed key-value data stores, like HBase, in order to benefit from the elastic scalability on offer. However, many applications still hesitate to make the leap from the traditional relational database model simply because they cannot compromise on the standard transactional guarantees of atomicity, isolation, and durability. To get the best of both worlds, one option is to integrate an independent transaction management component with a distributed key-value store. In this paper, we discuss the implications of this approach for durability. In particular, if the transaction manager provides durability (e.g., through logging), then we can relax durability constraints in the key-value store. However, if a component fails (e.g., a client or a key-value server), then we need a coordinated recovery procedure to ensure that commits are persisted correctly. In our research, we integrate an independent transaction manager with HBase. Our main contribution is a failure recovery middleware for the integrated system, which tracks the progress of each commit as it is flushed down by the client and persisted within HBase, so that we can recover reliably from failures. During recovery, commits that were interrupted by the failure are replayed from the transaction management log. Importantly, the recovery process does not interrupt transaction processing on the available servers. Using a benchmark, we evaluate the impact of component failure, and subsequent recovery, on application performance.

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Investment has declined in the euro area since the start of the economic and financial crisis, but this does not mean that there is necessarily an ‘investment gap’, explains Daniel Gros in this CEPS Policy Brief. Investment was probably above a sustainable level due to the credit boom before 2007. Moreover, the fall in the euro area’s potential growth − due to a combination of a sharp demographic slowdown and lower total factor productivity (TFP) growth − should also lead to a permanently lower investment rate. Increasing the investment rate might thus be the wrong target for economic policy. The author advises that the aim of economic policy should be to increase consumption, rather than investment overall. Increasing infrastructure investment might be justified in some member countries, but it is not a ‘free lunch’ when efficiency levels are low, which seems to be the case in some of the financially stressed euro area countries.

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This commentary finds that after four to five years of poor performance, final consumption of households is expected to recover significantly in 2015 and 2016. This is all the more important since final consumption of households was the main driver of economic growth during the 12 years preceding the financial crisis. Some obstacles still stand in the way, however, preventing a sustainable recovery in private consumption.

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Emotions play a significant role in the workplace, and considerable attention has been given to the study of employee emotions. Customers also play a central function in organizations, but much less is known about customer emotions. This chapter reviews the growing literature on customer emotions in employee–customer interfaces with a focus on service failure and recovery encounters, where emotions are heightened. It highlights emerging themes and key findings, addresses the measurement, modeling, and management of customer emotions, and identifies future research streams. Attention is given to emotional contagion, relationships between affective and cognitive processes, customer anger, customer rage, and individual differences.

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The importance of disturbance and the subsequent rate and pattern of recovery has been long recognised as an important driver of community structure. Community recovery is affected by processes operating at local and regional scales yet the examination of community level responses to a standardised disturbance at regional scales (i.e. among regions under different environmental conditions) has seldom been attempted. Here, we mechanically disturbed rocky intertidal lower shore algal dominated assemblages at three locations within each of three different regions within the Lusitanian biogeographical province (Azores, northern Portugal and the Canary Islands). All organisms were cleared from experimental plots and succession followed over a period of 12 months at which time we formally compared the assemblage structure to that of unmanipulated controls. Early patterns of recovery of disturbed communities varied among regions and was positively influenced by temperature, but not by regional species richness. Different components of the assemblage responded differently to disturbance. Regional differences in the relative abundance and identity of species had a key influence on the overall assemblage recovery. This study highlights how regional-scales differences in environmental conditions and species pool are important determinants of recovery of disturbed communities.

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Natural disasters are events that cause general and widespread destruction of the built environment and are becoming increasingly recurrent. They are a product of vulnerability and community exposure to natural hazards, generating a multitude of social, economic and cultural issues of which the loss of housing and the subsequent need for shelter is one of its major consequences. Nowadays, numerous factors contribute to increased vulnerability and exposure to natural disasters such as climate change with its impacts felt across the globe and which is currently seen as a worldwide threat to the built environment. The abandonment of disaster-affected areas can also push populations to regions where natural hazards are felt more severely. Although several actors in the post-disaster scenario provide for shelter needs and recovery programs, housing is often inadequate and unable to resist the effects of future natural hazards. Resilient housing is commonly not addressed due to the urgency in sheltering affected populations. However, by neglecting risks of exposure in construction, houses become vulnerable and are likely to be damaged or destroyed in future natural hazard events. That being said it becomes fundamental to include resilience criteria, when it comes to housing, which in turn will allow new houses to better withstand the passage of time and natural disasters, in the safest way possible. This master thesis is intended to provide guiding principles to take towards housing recovery after natural disasters, particularly in the form of flood resilient construction, considering floods are responsible for the largest number of natural disasters. To this purpose, the main structures that house affected populations were identified and analyzed in depth. After assessing the risks and damages that flood events can cause in housing, a methodology was proposed for flood resilient housing models, in which there were identified key criteria that housing should meet. The same methodology is based in the US Federal Emergency Management Agency requirements and recommendations in accordance to specific flood zones. Finally, a case study in Maldives – one of the most vulnerable countries to sea level rise resulting from climate change – has been analyzed in light of housing recovery in a post-disaster induced scenario. This analysis was carried out by using the proposed methodology with the intent of assessing the resilience of the newly built housing to floods in the aftermath of the 2004 Indian Ocean Tsunami.

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Among the numerous clinical syndromes observed after severe traumatic head injury, post-traumatic mutism is a disorder rarely reported in adults and not studied in any detail in children. We report seven children between the ages of 3 1/2 and 14 years who sustained severe head injury and developed post-traumatic mutism. We aim to give a precise clinical characterization of this disorder, discuss differential diagnosis and correlations with brain imaging and suggest its probable neurological substrate. After a coma lasting from 5 to 25 days, the seven patients who suffered from post-traumatic mutism went through a period of total absence of verbal production lasting from 5 to 94 days, associated with the recovery of non-verbal communication skills and emotional vocalization. During the first days after the recovery of speech, all patients were able to produce correct small sentences with a hypophonic and monotonous voice, moderate dysarthria, word finding difficulties but no signs of aphasia, and preserved oral comprehension. The neurological signs in the acute phase (III nerve paresis in three of seven patients, signs of autonomic dysfunctions in five of seven patients), the results of the brain imaging and the experimental animal data all suggest the involvement of mesencephalic structures as playing a key role in the aetiology of post-traumatic mutism.

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The "State of Iowa Long-Term Economic Recovery Strategy" was prepared for the Economic Development Administration, U.S. Department of Commerce. In July, 2008 Iowa received a $3 million grant from the Economic Development Administration to create an Economic Recovery Strategy for recovering from the devastating floods and tornadoes that impacted the state earlier that summer. This report outlines the final version of that strategy. It includes the methods, goals, objectives, measures and key projects that the state has undertaken and will continue into the future to ensure the state‘s complete recovery.