948 resultados para flash crowd attack


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This article analyses the legality of Israel’s 2007 airstrike on an alleged Syrian nuclear facility at Al-Kibar—an incident that has been largely overlooked by international lawyers to date. The absence of a threat of imminent attack from Syria means Israel’s military action was not a lawful exercise of anticipatory self-defence. Yet, despite Israel’s clear violation of the prohibition on the use of force there was remarkably little condemnation from other states, suggesting the possibility of growing international support for the doctrine of pre-emptive self-defence. This article argues that the muted international reaction to Israel’s pre-emptive action was the result of political factors, and should not be seen as endorsement of the legality of the airstrike. As such, a lack of opinio juris means the Al-Kibar episode cannot be viewed as extending the scope of the customary international law right of self-defence so as to permit the use of force against non-imminent threats. However, two features of this incident—namely, Israel’s failure to offer any legal justification for its airstrike, and the international community’s apparent lack of concern over legality—are also evident in other recent uses of force in the ‘war on terror’ context. These developments may indicate a shift in state practice involving a downgrading of the role of international law in discussions of the use of force. This may signal a declining perception of the legitimacy of the jus ad bellum, at least in cases involving minor uses of force.

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Despite the conventional wisdom that proactive security is superior to reactive security, we show that reactive security can be competitive with proactive security as long as the reactive defender learns from past attacks instead of myopically overreacting to the last attack. Our game-theoretic model follows common practice in the security literature by making worst-case assumptions about the attacker: we grant the attacker complete knowledge of the defender’s strategy and do not require the attacker to act rationally. In this model, we bound the competitive ratio between a reactive defense algorithm (which is inspired by online learning theory) and the best fixed proactive defense. Additionally, we show that, unlike proactive defenses, this reactive strategy is robust to a lack of information about the attacker’s incentives and knowledge.

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Machine learning has become a valuable tool for detecting and preventing malicious activity. However, as more applications employ machine learning techniques in adversarial decision-making situations, increasingly powerful attacks become possible against machine learning systems. In this paper, we present three broad research directions towards the end of developing truly secure learning. First, we suggest that finding bounds on adversarial influence is important to understand the limits of what an attacker can and cannot do to a learning system. Second, we investigate the value of adversarial capabilities-the success of an attack depends largely on what types of information and influence the attacker has. Finally, we propose directions in technologies for secure learning and suggest lines of investigation into secure techniques for learning in adversarial environments. We intend this paper to foster discussion about the security of machine learning, and we believe that the research directions we propose represent the most important directions to pursue in the quest for secure learning.

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Data preprocessing is widely recognized as an important stage in anomaly detection. This paper reviews the data preprocessing techniques used by anomaly-based network intrusion detection systems (NIDS), concentrating on which aspects of the network traffic are analyzed, and what feature construction and selection methods have been used. Motivation for the paper comes from the large impact data preprocessing has on the accuracy and capability of anomaly-based NIDS. The review finds that many NIDS limit their view of network traffic to the TCP/IP packet headers. Time-based statistics can be derived from these headers to detect network scans, network worm behavior, and denial of service attacks. A number of other NIDS perform deeper inspection of request packets to detect attacks against network services and network applications. More recent approaches analyze full service responses to detect attacks targeting clients. The review covers a wide range of NIDS, highlighting which classes of attack are detectable by each of these approaches. Data preprocessing is found to predominantly rely on expert domain knowledge for identifying the most relevant parts of network traffic and for constructing the initial candidate set of traffic features. On the other hand, automated methods have been widely used for feature extraction to reduce data dimensionality, and feature selection to find the most relevant subset of features from this candidate set. The review shows a trend toward deeper packet inspection to construct more relevant features through targeted content parsing. These context sensitive features are required to detect current attacks.

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Emotional responses can incite and entice consumers to select a particular product from a row of similar items and thus have a considerable impact on purchase decisions. Consequently, more and more companies are challenging designers to address the emotional impact of their work and to design for emotion and consumerproduct relationships. Furthermore, the creation of emotional attachment to one’s possessions is one way of approaching a sustainable consumer-product relationship. The aim of this research is to gain a deeper understanding of the instantaneous emotional attachment that consumers form with products and its subsequent implications for product development. The foci of the study are visceral design, consumer hedonics and product rhetoric. Studied in a conglomerate they become an area of new investigation: visceral hedonic rhetoric. In this context, the term “visceral hedonic rhetoric” is defined as the properties of a product that persuasively elicit the pursuit of pleasure at an instinctual level of cognition. This study explores visceral hedonic rhetoric evident in the design of interactive products and resides within the context of emotional design research. It employs an empirical approach to understand how consumers respond hedonically on a visceral level to rhetoric in products. Specifically, it examines visceral hedonic responses given by thirty participants to the stimuli of six mobile telephones, six Mp3 players and six USB memory flash drives. The study findings demonstrate a hierarchy of visceral hedonic rhetoric evident in interactive products. This hierarchy of visceral hedonic attributes include: colour, size, shape, intrigue, material, perceived usability, portability, perceived function, novelty, analogy, brand, quality, texture and gender. However, it is the interrelationships between these visceral hedonic attributes that are the most significant findings of this research. Certain associations were revealed between product attribute combinations and consumer perception. The most predominant of these were: gender bias associated with colour selection; the creation of intrigue through a vibrant attention-grabbing colour; perceived ease of use and function; product confidence as a result of brand familiarity and perceived usability; analogous association through familiarity with similar objects and shapes; and the association of longevity with quality, novelty or recent technology. A significant outcome of the research is the distillation of visceral hedonic rhetoric design principles, and a tool to assist designers in harnessing the full potential of visceral hedonic rhetoric. This study contributes to the identification of the emerging research field of visceral hedonic rhetoric. Application of this study’s findings has the potential to provide a hedonic consumer-product relationship that is more meaningful, less disposable and more sustainable. This theory of visceral hedonic rhetoric is not only a significant contribution to design knowledge but is also generally transferable to other research domains, as later suggested in future research avenues.

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There are many applications in aeronautical/aerospace engineering where some values of the design parameters states cannot be provided or determined accurately. These values can be related to the geometry(wingspan, length, angles) and or to operational flight conditions that vary due to the presence of uncertainty parameters (Mach, angle of attack, air density and temperature, etc.). These uncertainty design parameters cannot be ignored in engineering design and must be taken into the optimisation task to produce more realistic and reliable solutions. In this paper, a robust/uncertainty design method with statistical constraints is introduced to produce a set of reliable solutions which have high performance and low sensitivity. Robust design concept coupled with Multi Objective Evolutionary Algorithms (MOEAs) is defined by applying two statistical sampling formulas; mean and variance/standard deviation associated with the optimisation fitness/objective functions. The methodology is based on a canonical evolution strategy and incorporates the concepts of hierarchical topology, parallel computing and asynchronous evaluation. It is implemented for two practical Unmanned Aerial System (UAS) design problems; the flrst case considers robust multi-objective (single disciplinary: aerodynamics) design optimisation and the second considers a robust multidisciplinary (aero structures) design optimisation. Numerical results show that the solutions obtained by the robust design method with statistical constraints have a more reliable performance and sensitivity in both aerodynamics and structures when compared to the baseline design.

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Measuring the business value that Internet technologies deliver for organisations has proven to be a difficult and elusive task, given their complexity and increased embeddedness within the value chain. Yet, despite the lack of empirical evidence that links the adoption of Information Technology (IT) with increased financial performance, many organisations continue to adopt new technologies at a rapid rate. This is evident in the widespread adoption of Web 2.0 online Social Networking Services (SNSs) such as Facebook, Twitter and YouTube. These new Internet based technologies, widely used for social purposes, are being employed by organisations to enhance their business communication processes. However, their use is yet to be correlated with an increase in business performance. Owing to the conflicting empirical evidence that links prior IT applications with increased business performance, IT, Information Systems (IS), and E-Business Model (EBM) research has increasingly looked to broader social and environmental factors as a means for examining and understanding the broader influences shaping IT, IS and E-Business (EB) adoption behaviour. Findings from these studies suggest that organisations adopt new technologies as a result of strong external pressures, rather than a clear measure of enhanced business value. In order to ascertain if this is the case with the adoption of SNSs, this study explores how organisations are creating value (and measuring that value) with the use of SNSs for business purposes, and the external pressures influencing their adoption. In doing so, it seeks to address two research questions: 1. What are the external pressures influencing organisations to adopt SNSs for business communication purposes? 2. Are SNSs providing increased business value for organisations, and if so, how is that value being captured and measured? Informed by the background literature fields of IT, IS, EBM, and Web 2.0, a three-tiered theoretical framework is developed that combines macro-societal, social and technological perspectives as possible causal mechanisms influencing the SNS adoption event. The macro societal view draws on the concept of Castells. (1996) network society and the behaviour of crowds, herds and swarms, to formulate a new explanatory concept of the network vortex. The social perspective draws on key components of institutional theory (DiMaggio & Powell, 1983, 1991), and the technical view draws from the organising vision concept developed by Swanson and Ramiller (1997). The study takes a critical realist approach, and conducts four stages of data collection and one stage of data coding and analysis. Stage 1 consisted of content analysis of websites and SNSs of many organisations, to identify the types of business purposes SNSs are being used for. Stage 2 also involved content analysis of organisational websites, in order to identify suitable sample organisations in which to conduct telephone interviews. Stage 3 consisted of conducting 18 in-depth, semi-structured telephone interviews within eight Australian organisations from the Media/Publishing and Galleries, Libraries, Archives and Museum (GLAM) industries. These sample organisations were considered leaders in the use of SNSs technologies. Stage 4 involved an SNS activity count of the organisations interviewed in Stage 3, in order to rate them as either Advanced Innovator (AI) organisations, or Learning Focussed (LF) organisations. A fifth stage of data coding and analysis of all four data collection stages was conducted, based on the theoretical framework developed for the study, and using QSR NVivo 8 software. The findings from this study reveal that SNSs have been adopted by organisations for the purpose of increasing business value, and as a result of strong social and macro-societal pressures. SNSs offer organisations a wide range of value enhancing opportunities that have broader benefits for customers and society. However, measuring the increased business value is difficult with traditional Return On Investment (ROI) mechanisms, ascertaining the need for new value capture and measurement rationales, to support the accountability of SNS adoption practices. The study also identified the presence of technical, social and macro-societal pressures, all of which influenced SNS adoption by organisations. These findings contribute important theoretical insight into the increased complexity of pressures influencing technology adoption rationales by organisations, and have important practical implications for practice, by reflecting the expanded global online networks in which organisations now operate. The limitations of the study include the small number of sample organisations in which interviews were conducted, its limited generalisability, and the small range of SNSs selected for the study. However, these were compensated in part by the expertise of the interviewees, and the global significance of the SNSs that were chosen. Future research could replicate the study to a larger sample from different industries, sectors and countries. It could also explore the life cycle of SNSs in a longitudinal study, and map how the technical, social and macro-societal pressures are emphasised through stages of the life cycle. The theoretical framework could also be applied to other social fad technology adoption studies.

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Airports worldwide represent key forms of critical infrastructure in addition to serving as nodes in the international aviation network. While the continued operation of airports is critical to the functioning of reliable air passenger and freight transportation, these infrastructure systems face a number of sources of disturbance that threaten their operational viability. Recent examples of high magnitude events include the eruption of Iceland’s Eyjafjallajokull volcano eruption (Folattau and Schofield 2010), the failure of multiple systems at the opening of Heathrow’s Terminal 5 (Brady and Davies 2010) and the Glasgow airport 2007 terrorist attack (Crichton 2008). While these newsworthy events do occur, a multitude of lower-level more common disturbances also have the potential to cause significant discontinuity to airport operations. Regional airports face a unique set of challenges, particularly in a nation like Australia where they serve to link otherwise remote and isolated communities to metropolitan hubs (Wheeler 2005), often without the resources and political attention received by larger capital city airports. This paper discusses conceptual relationships between Business Continuity Management (BCM) and High Reliability Theory, and proposes BCM as an appropriate risk-based management process to ensure continued airport operation in the face of uncertainty. In addition, it argues that that correctly implemented BCM can lead to highly reliable organisations. This is framed within the broader context of critical infrastructures and the need for adequate crisis management approaches suited to their unique requirements (Boin and McConnell 2007).

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Crowdsourcing harnesses the potential of large and open networks of people. It is a relatively new phenomenon and attracted substantial interest in practice. Related research, however, lacks a theoretical foundation. We propose a system-theoretical perspective on crowdsourcing systems to address this gap and illustrate its applicability by using it to classify crowdsourcing systems. By deriving two principal dimensions from theory, we identify four fundamental types of crowdsourcing systems that help to distinguish important features of such systems. We analyse their respective characteristics and discuss implications and requirements for various aspects related to the design of such systems. Our results demonstrate that systems theory can inform the study of crowdsourcing systems. The identified system types and the implications on their design may prove useful for researchers to frame future studies and for practitioners to identify the right crowdsourcing systems for a particular purpose.

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Client puzzles are moderately-hard cryptographic problems neither easy nor impossible to solve that can be used as a counter-measure against denial of service attacks on network protocols. Puzzles based on modular exponentiation are attractive as they provide important properties such as non-parallelisability, deterministic solving time, and linear granularity. We propose an efficient client puzzle based on modular exponentiation. Our puzzle requires only a few modular multiplications for puzzle generation and verification. For a server under denial of service attack, this is a significant improvement as the best known non-parallelisable puzzle proposed by Karame and Capkun (ESORICS 2010) requires at least 2k-bit modular exponentiation, where k is a security parameter. We show that our puzzle satisfies the unforgeability and difficulty properties defined by Chen et al. (Asiacrypt 2009). We present experimental results which show that, for 1024-bit moduli, our proposed puzzle can be up to 30 times faster to verify than the Karame-Capkun puzzle and 99 times faster than the Rivest et al.'s time-lock puzzle.

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Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

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Key establishment is a crucial cryptographic primitive for building secure communication channels between two parties in a network. It has been studied extensively in theory and widely deployed in practice. In the research literature a typical protocol in the public-key setting aims for key secrecy and mutual authentication. However, there are many important practical scenarios where mutual authentication is undesirable, such as in anonymity networks like Tor, or is difficult to achieve due to insufficient public-key infrastructure at the user level, as is the case on the Internet today. In this work we are concerned with the scenario where two parties establish a private shared session key, but only one party authenticates to the other; in fact, the unauthenticated party may wish to have strong anonymity guarantees. We present a desirable set of security, authentication, and anonymity goals for this setting and develop a model which captures these properties. Our approach allows for clients to choose among different levels of authentication. We also describe an attack on a previous protocol of Øverlier and Syverson, and present a new, efficient key exchange protocol that provides one-way authentication and anonymity.

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The researcher was invited to photograph athletes in the lead-up to the 2006 Commonwealth Games held in Melbourne. She photographed four indigenous athletes, to produce a series of four large-scale cotton rag prints, 1 meter x 1 meter, printed onto photorag paper from digital files. “My photographic practice can be described as both political and spiritual, in the sense that as an Aboriginal Indigenous artist I take stock of the rationalising effect of the technologies I use, and create work that evokes nature and spirit. My methods often involve re-photographing or digitally re-working landscape photographs and adding historical or cultural icons of significance. Working with Indigenous athletes has been an honour and a pleasure. I admire the athletes’ passion and dedication to their chosen sport, and above all their humility, which seems a trait somewhat in contrast to what it takes to attain the highest levels of achievement. Indigenous athletes are wonderful role models for all Australians, and in making creative work that places their luminary presence with the land, I am aligning sportspeople with a deep sense of nature and spirit.” – Leah King-Smith. These works were commissioned by the National Portrait Gallery for the exhibition FLASH: Australian Athletes in Focus. The exhibition was a significant element in Melbourne2006 Festival, the cultural festival of the Commonwealth Games. The exhibition was prominently reviewed in Portrait: Magazine of Australian and International Portraiture and was subsequently remounted at Old Parliament House, Canberra (15 July to 12 November, 2006). One image was used for the front cover of Art Monthly, (March 2006).

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Existing algebraic analyses of the ZUC cipher indicate that the cipher should be secure against algebraic attacks. In this paper, we present an alternative algebraic analysis method for the ZUC stream cipher, where a combiner is used to represent the nonlinear function and to derive equations representing the cipher. Using this approach, the initial states of ZUC can be recovered from 2^97 observed words of keystream, with a complexity of 2^282 operations. This method is more successful when applied to a modified version of ZUC, where the number of output words per clock is increased. If the cipher outputs 120 bits of keystream per clock, the attack can succeed with 219 observed keystream bits and 2^47 operations. Therefore, the security of ZUC against algebraic attack could be significantly reduced if its throughput was to be increased for efficiency.

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Both the SSS and SOBER-t32 stream cipher designs use a single word-based shift register and a nonlinear filter function to produce keystream. In this paper we show that the algebraic attack method previously applied to SOBER-t32 is prevented from succeeding on SSS by the use of the key dependent substitution box (SBox) in the nonlinear filter of SSS. Additional assumptions and modifications to the SSS cipher in an attempt to enable algebraic analysis result in other difficulties that also render the algebraic attack infeasible. Based on these results, we conclude that a well chosen key-dependent substitution box used in the nonlinear filter of the stream cipher provides resistance against such algebraic attacks.