Effects of transportation accessibility on residential property values: Application of spatial hedonic price model in Seoul, South Korea, metropolitan area

A number of studies have focused on estimating the effects of accessibility on housing values by using the hedonic price model. In the majority of studies, estimation results have revealed that housing values increase as accessibility improves, although the magnitude of estimates has varied across studies. Adequately estimating the relationship between transportation accessibility and housing values is challenging for at least two reasons. First, the monocentric city assumption applied in location theory is no longer valid for many large or growing cities. Second, rather than being randomly distributed in space, housing values are clustered in space—often exhibiting spatial dependence. Recognizing these challenges, a study was undertaken to develop a spatial lag hedonic price model in the Seoul, South Korea, metropolitan region, which includes a measure of local accessibility as well as systemwide accessibility, in addition to other model covariates. Although the accessibility measures can be improved, the modeling results suggest that the spatial interactions of apartment sales prices occur across and within traffic analysis zones, and the sales prices for apartment communities are devalued as accessibility deteriorates. Consistent with findings in other cities, this study revealed that the distance to the central business district is still a significant determinant of sales price.

Developing a simulator application to test the billing platform in telecom industry

Billing Mediation Platform (BMP) in telecommunication industry is used to process real-time streams of Call Detail Records (CDRs) which can be a massive number a day. The generated records by BMP can be deployed for billing purposes, fraud detection, spam filtering, traffic analysis, and churn forecast. Several of these applications are distinguished by real-time processing requiring low-latency analysis of CDRs. Testing of such a platform carries diverse aspects like stress testing of analytics for scalability and what-if scenarios which require generating of CDRs with realistic volumetric and appropriate properties. The approach of this project is to build user friendly and flexible application which assists the development department to test their billing solution occasionally. These generators projects have been around for a while the only difference are the potions they cover and the purpose they will be used for. This paper proposes to use a simulator application to test the BMPs with simulating CDRs. The Simulated CDRs are modifiable based on the user requirements and represent real world data.

Ensemble-based DDoS detection and mitigation model

This work-in-progress paper presents an ensemble-based model for detecting and mitigating Distributed Denial-of-Service (DDoS) attacks, and its partial implementation. The model utilises network traffic analysis and MIB (Management Information Base) server load analysis features for detecting a wide range of network and application layer DDoS attacks and distinguishing them from Flash Events. The proposed model will be evaluated against realistic synthetic network traffic generated using a software-based traffic generator that we have developed as part of this research. In this paper, we summarise our previous work, highlight the current work being undertaken along with preliminary results obtained and outline the future directions of our work.

Application-level simulation for network security

NeSSi (network security simulator) is a novel network simulation tool which incorporates a variety of features relevant to network security distinguishing it from general-purpose network simulators. Its capabilities such as profile-based automated attack generation, traffic analysis and support for detection algorithm plug-ins allow it to be used for security research and evaluation purposes. NeSSi has been successfully used for testing intrusion detection algorithms, conducting network security analysis and developing overlay security frameworks. NeSSi is built upon the agent framework JIAC, resulting in a distributed and extensible architecture. In this paper, we provide an overview of the NeSSi architecture as well as its distinguishing features and briefly demonstrate its application to current security research projects.

Bayesian imputation of non-chosen attribute values in revealed preference surveys

Obtaining attribute values of non-chosen alternatives in a revealed preference context is challenging because non-chosen alternative attributes are unobserved by choosers, chooser perceptions of attribute values may not reflect reality, existing methods for imputing these values suffer from shortcomings, and obtaining non-chosen attribute values is resource intensive. This paper presents a unique Bayesian (multiple) Imputation Multinomial Logit model that imputes unobserved travel times and distances of non-chosen travel modes based on random draws from the conditional posterior distribution of missing values. The calibrated Bayesian (multiple) Imputation Multinomial Logit model imputes non-chosen time and distance values that convincingly replicate observed choice behavior. Although network skims were used for calibration, more realistic data such as supplemental geographically referenced surveys or stated preference data may be preferred. The model is ideally suited for imputing variation in intrazonal non-chosen mode attributes and for assessing the marginal impacts of travel policies, programs, or prices within traffic analysis zones.

Component modeling for SCADA network mapping

Supervisory Control and Data Acquisition systems (SCADA) are widely used to control critical infrastructure automatically. Capturing and analyzing packet-level traffic flowing through such a network is an essential requirement for problems such as legacy network mapping and fault detection. Within the framework of captured network traffic, we present a simple modeling technique, which supports the mapping of the SCADA network topology via traffic monitoring. By characterizing atomic network components in terms of their input-output topology and the relationship between their data traffic logs, we show that these modeling primitives have good compositional behaviour, which allows complex networks to be modeled. Finally, the predictions generated by our model are found to be in good agreement with experimentally obtained traffic.

基于序贯模式挖掘的宏观网络流量异常检测

基于序贯频繁模式挖掘，提出并实现了一种宏观网络流量异常检测的方法。定义了一个新的频繁模式和相对应的异常度概念。对863—917网络安全监测平台提供的全国流量数据进行了实验，得出对应于“橙色八月”的2006年8月上旬流量严重异常的结论。通过与相关的其他传统算法进行对比，如使用绝对流量的算法和简单使用不同小时流量排名的算法，进一步说明序贯频繁模式对网络流量分析的实用性。

Resource Management for Responsive Web Computing

The exploding demand for services like the World Wide Web reflects the potential that is presented by globally distributed information systems. The number of WWW servers world-wide has doubled every 3 to 5 months since 1993, outstripping even the growth of the Internet. At each of these self-managed sites, the Common Gateway Interface (CGI) and Hypertext Transfer Protocol (HTTP) already constitute a rudimentary basis for contributing local resources to remote collaborations. However, the Web has serious deficiencies that make it unsuited for use as a true medium for metacomputing --- the process of bringing hardware, software, and expertise from many geographically dispersed sources to bear on large scale problems. These deficiencies are, paradoxically, the direct result of the very simple design principles that enabled its exponential growth. There are many symptoms of the problems exhibited by the Web: disk and network resources are consumed extravagantly; information search and discovery are difficult; protocols are aimed at data movement rather than task migration, and ignore the potential for distributing computation. However, all of these can be seen as aspects of a single problem: as a distributed system for metacomputing, the Web offers unpredictable performance and unreliable results. The goal of our project is to use the Web as a medium (within either the global Internet or an enterprise intranet) for metacomputing in a reliable way with performance guarantees. We attack this problem one four levels: (1) Resource Management Services: Globally distributed computing allows novel approaches to the old problems of performance guarantees and reliability. Our first set of ideas involve setting up a family of real-time resource management models organized by the Web Computing Framework with a standard Resource Management Interface (RMI), a Resource Registry, a Task Registry, and resource management protocols to allow resource needs and availability information be collected and disseminated so that a family of algorithms with varying computational precision and accuracy of representations can be chosen to meet realtime and reliability constraints. (2) Middleware Services: Complementary to techniques for allocating and scheduling available resources to serve application needs under realtime and reliability constraints, the second set of ideas aim at reduce communication latency, traffic congestion, server work load, etc. We develop customizable middleware services to exploit application characteristics in traffic analysis to drive new server/browser design strategies (e.g., exploit self-similarity of Web traffic), derive document access patterns via multiserver cooperation, and use them in speculative prefetching, document caching, and aggressive replication to reduce server load and bandwidth requirements. (3) Communication Infrastructure: Finally, to achieve any guarantee of quality of service or performance, one must get at the network layer that can provide the basic guarantees of bandwidth, latency, and reliability. Therefore, the third area is a set of new techniques in network service and protocol designs. (4) Object-Oriented Web Computing Framework A useful resource management system must deal with job priority, fault-tolerance, quality of service, complex resources such as ATM channels, probabilistic models, etc., and models must be tailored to represent the best tradeoff for a particular setting. This requires a family of models, organized within an object-oriented framework, because no one-size-fits-all approach is appropriate. This presents a software engineering challenge requiring integration of solutions at all levels: algorithms, models, protocols, and profiling and monitoring tools. The framework captures the abstract class interfaces of the collection of cooperating components, but allows the concretization of each component to be driven by the requirements of a specific approach and environment.

Secure Virtualised Environment

Cloud computing is a technological advancementthat provide resources through internet on pay-as-you-go basis.Cloud computing uses virtualisation technology to enhance theefficiency and effectiveness of its advantages. Virtualisation isthe key to consolidate the computing resources to run multiple instances on each hardware, increasing the utilization rate of every resource, thus reduces the number of resources needed to buy, rack, power, cool, and manage. Cloud computing has very appealing features, however, lots of enterprises and users are still reluctant to move into cloud due to serious security concerns related to virtualisation layer. Thus, it is foremost important to secure the virtual environment.In this paper, we present an elastic framework to secure virtualised environment for trusted cloud computing called Server Virtualisation Security System (SVSS). SVSS provide security solutions located on hyper visor for Virtual Machines by deploying malicious activity detection techniques, network traffic analysis techniques, and system resource utilization analysis techniques.SVSS consists of four modules: Anti-Virus Control Module,Traffic Behavior Monitoring Module, Malicious Activity Detection Module and Virtualisation Security Management Module.A SVSS prototype has been deployed to validate its feasibility,efficiency and accuracy on Xen virtualised environment.

Análise do desempenho de autoestradas através de microssimulação

Portugal é um dos países europeus com melhor cobertura espacial e populacional de rede de autoestradas (5º entre os 27 da UE). O acentuado crescimento desta rede nos últimos anos leva a que seja necessária a utilização de metodologias de análise e avaliação da qualidade do serviço que é prestado nestas infraestruturas, relativamente às condições de circulação. Usualmente, a avaliação da qualidade de serviço é efetuada por intermédio de metodologias internacionalmente aceites, das quais se destaca a preconizada no Highway Capacity Manual (HCM). É com esta última metodologia que são habitualmente determinados em Portugal, os níveis de serviço nas diversas componentes de uma autoestrada (secções correntes, ramos de ligação e segmentos de entrecruzamento). No entanto, a sua transposição direta para a realidade portuguesa levanta algumas reservas, uma vez que os elementos que compõem o ambiente rodoviário (infraestrutura, veículo e condutor) são distintos dos da realidade norte-americana para a qual foi desenvolvida. Assim, seria útil para os atores envolvidos no setor rodoviário dispor de metodologias desenvolvidas para as condições portuguesas, que possibilitassem uma caracterização mais realista da qualidade de serviço ao nível da operação em autoestradas. No entanto, importa referir que o desenvolvimento de metodologias deste género requer uma quantidade muito significativa de dados geométricos e de tráfego, o que acarreta uma enorme necessidade de meios, quer humanos, quer materiais. Esta abordagem é assim de difícil execução, sendo por isso necessário recorrer a metodologias alternativas para a persecução deste objetivo. Ultimamente tem-se verificado o uso cada vez mais generalizado de modelos de simulação microscópica de tráfego, que simulando o movimento individual dos veículos num ambiente virtual permitem realizar análises de tráfego. A presente dissertação apresenta os resultados obtidos no desenvolvimento de uma metodologia que procura recriar, através de simuladores microscópicos de tráfego, o comportamento das correntes de tráfego em secções correntes de autoestradas com o intuito de, posteriormente, se proceder à adaptação da metodologia preconizada no HCM (na sua edição de 2000) à realidade portuguesa. Para tal, com os simuladores microscópicos utilizados (AIMSUN e VISSIM) procurou-se reproduzir as condições de circulação numa autoestrada portuguesa, de modo a que fosse possível analisar as alterações sofridas no comportamento das correntes de tráfego após a modificação dos principais fatores geométricos e de tráfego envolvidos na metodologia do HCM 2000. Para o efeito, realizou-se uma análise de sensibilidade aos simuladores de forma a avaliar a sua capacidade para representar a influência desses fatores, com vista a, numa fase posterior, se quantificar o seu efeito para a realidade nacional e dessa forma se proceder à adequação da referida metodologia ao contexto português. Em resumo, o presente trabalho apresenta as principais vantagens e limitações dos microssimuladores AIMSUN e VISSIM na modelação do tráfego de uma autoestrada portuguesa, tendo-se concluído que estes simuladores não são capazes de representar de forma explícita alguns dos fatores considerados na metodologia do HCM 2000, o que impossibilita a sua utilização como ferramenta de quantificação dos seus efeitos e consequentemente inviabiliza a adaptação dessa metodologia à realidade nacional. São, no entanto, referidas algumas indicações de como essas limitações poderão vir a ser ultrapassadas, com vista à consecução futura dessa adequação.

Chuckle Brothers INFO2009 CW2

Resource, Poster and Reference for the coursework

Avaliação da tecnologia femtocell como canal de retorno para TV digital

Mensurar os impactos do tráfego de aplicações interativas para TV Digital nas redes sem fio de 4a geração em especial WIMAX e femtocell tem sido um grande desafio para pesquisadores em todo o mundo, o teste destas tecnologias se mostra promissora para a melhor qualidade de serviço prestado pelas operadoras. Inicialmente, identificando o padrão de tráfego de rede através da aferição e caracterização de tráfego de uma aplicação interativa de TV Digital do Sistema Brasileiro de TV Digital (SBTVD). A partir de então, as simulações são feitas sobre uma rede sem fio. Para este estudo, a rede WiMAX foi escolhida como um de nossos estudo de caso. Um estudo dos impactos do uso desta aplicação em uma WMAN (Wireless Metropolitan Área Network) com WiMAX e também utilizando femtocells. Evidentemente, tecnologias sem fio apresentam uma grande variação da qualidade do sinal. Deste modo, é necessário utilizar uma solução para reduzir essa degradação no sinal. Dentre as possíveis soluções, o uso de femtocells surge como alternativa viável para estas melhorias, lembrando que uso de femtocell esta diretamente ligado para áreas onde o sinal é zero ou muito baixo. A utilização de simulações discretas através de ferramentas apropriadas como o OPNET, se mostram bastante úteis para viabilizar a utilização das tecnologias existentes, expondo-as a condições mais adversas de fluxo, carga , numero de usuários e distancias que certamente influenciam no desempenha de cada uma delas.

Scheduling application-aware in piattaforme di stream processing distribuito per scenari smart city

In piattaforme di Stream Processing è spesso necessario eseguire elaborazioni differenziate degli stream di input. Questa tesi ha l'obiettivo di realizzare uno scheduler in grado di attribuire priorità di esecuzione differenti agli operatori deputati all'elaborazione degli stream.

Tor network forensics and hidden service deanonymization

The cybernetics revolution of the last years improved a lot our lives, having an immediate access to services and a huge amount of information over the Internet. Nowadays the user is increasingly asked to insert his sensitive information on the Internet, leaving its traces everywhere. But there are some categories of people that cannot risk to reveal their identities on the Internet. Even if born to protect U.S. intelligence communications online, nowadays Tor is the most famous low-latency network, that guarantees both anonymity and privacy of its users. The aim of this thesis project is to well understand how the Tor protocol works, not only studying its theory, but also implementing those concepts in practice, having a particular attention for security topics. In order to run a Tor private network, that emulates the real one, a virtual testing environment has been configured. This behavior allows to conduct experiments without putting at risk anonymity and privacy of real users. We used a Tor patch, that stores TLS and circuit keys, to be given as inputs to a Tor dissector for Wireshark, in order to obtain decrypted and decoded traffic. Observing clear traffic allowed us to well check the protocol outline and to have a proof of the format of each cell. Besides, these tools allowed to identify a traffic pattern, used to conduct a traffic correlation attack to passively deanonymize hidden service clients. The attacker, controlling two nodes of the Tor network, is able to link a request for a given hidden server to the client who did it, deanonymizing him. The robustness of the traffic pattern and the statistics, such as the true positive rate, and the false positive rate, of the attack are object of a potential future work.

Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain

Improving the knowledge of demand evolution over time is a key aspect in the evaluation of transport policies and in forecasting future investment needs. It becomes even more critical for the case of toll roads, which in recent decades has become an increasingly common device to fund road projects. However, literature regarding demand elasticity estimates in toll roads is sparse and leaves some important aspects to be analyzed in greater detail. In particular, previous research on traffic analysis does not often disaggregate heavy vehicle demand from the total volume, so that the specific behavioral patternsof this traffic segment are not taken into account. Furthermore, GDP is the main socioeconomic variable most commonly chosen to explain road freight traffic growth over time. This paper seeks to determine the variables that better explain the evolution of heavy vehicle demand in toll roads over time. To that end, we present a dynamic panel data methodology aimed at identifying the key socioeconomic variables that explain the behavior of road freight traffic throughout the years. The results show that, despite the usual practice, GDP may not constitute a suitable explanatory variable for heavy vehicle demand. Rather, considering only the GDP of those sectors with a high impact on transport demand, such as construction or industry, leads to more consistent results. The methodology is applied to Spanish toll roads for the 1990?2011 period. This is an interesting case in the international context, as road freight demand has experienced an even greater reduction in Spain than elsewhere, since the beginning of the economic crisis in 2008.