Spam emails are flooding the Internet. Research to prevent spam is an ongoing concern. SMTP traffic was collected from different sources in real networks and analyzed to determine the difference regarding SMTP traffic characteristics of legitimate email clients, legitimate email servers and spam relays. It is found that SMTP traffic from legitimate sites and non-legitimate sites are different and could be distinguished from each other. Some methods, which are based on analyzing SMTP traffic characteristics, were purposed to identify spam relays in the network in this thesis. An autonomous combination system, in which machine learning technologies were employed, was developed to identify spam relays in this thesis. This system identifies spam relays in real time before spam emails get to an end user by using SMTP traffic characteristics never involving email real content. A series of tests were conducted to evaluate the performance of this system. And results show that the system can identify spam relays with a high spam relay detection rate and an acceptable ratio of false positive errors.

Over the last few decades, the Internet ecosystem has been continuously evolving to meet the demands of its ever-increasing user base. Drastic changes in the Internet infrastructure have improved its capacity and throughput performance, enabling a wealth of new services. For Internet Service Providers (ISPs), anticipating and accommodating the rapidly shifting traffic demands has been a technological, economical, and political challenge. Thus far, this challenge has been met in an "organic" fashion, for the most part, based on unilateral actions of many different players such as ISPs, content providers, public policy makers, international organizations, and large enterprises. This symbiotic relationship among many and often competing change factors has led to a system of enormous complexity that was not a product of well-founded engineering principles. Despite the continuous efforts of the scientific and enterprise communities to discover and to model the Internet, understanding its structure remains a hard challenge. In this thesis, we provide a new perspective on the Internet's evolutionary pat- terns at the Autonomous System (AS) level. While many studies have focused on the mathematical models that express the growth of the AS graph topology as a whole, little research has been performed to correlate this growth with geographic, economic, and political data, as well as related business interests. We divide the Internet to five distinct regions using the well-established Internet registry classification and show that the structural properties and evolutionary patterns differ from region to region. We further analyze the business relationships that dominate each region, as well relationships between regions. Conclusions from our analysis is used to explain global as well as local Internet structure phenomena.

This dissertation presents measures of efficiency and locality for Internet addressing schemes. Historically speaking, many issues, faced by the Internet, have been solved just in time, to make the Internet just work~\cite{justWork}. Consensus, however, has been reached that today's Internet routing and addressing system is facing serious scaling problems: multi-homing which causes finer granularity of routing policies and finer control to realize various traffic engineering requirements, an increased demand for provider-independent prefix allocations which injects unaggregatable prefixes into the Default Free Zone (DFZ) routing table, and ever-increasing Internet user population and mobile edge devices. As a result, the DFZ routing table is again growing at an exponential rate. Hierarchical, topology-based addressing has long been considered crucial to routing and forwarding scalability. Recently, however, a number of research efforts are considering alternatives to this traditional approach. With the goal of informing such research, we investigated the efficiency of address assignment in the existing (IPv4) Internet. In particular, we ask the question: ``how can we measure the locality of an address scheme given an input AS-level graph?'' To do so, we first define a notion of efficiency or locality based on the average number of bit-hops required to advertize all prefixes in the Internet. In order to quantify how far from ``optimal" the current Internet is, we assign prefixes to ASes ``from scratch" in a manner that preserves observed semantics, using three increasingly strict definitions of equivalence. Next we propose another metric that in some sense quantifies the ``efficiency" of the labeling and is independent of forwarding/routing mechanisms. We validate the effectiveness of the metric by applying it to a series of address schemes with increasing randomness given an input AS-level graph. After that we apply the metric to the current Internet address scheme across years and compare the results with those of compact routing schemes.

Submitted by Daniella Santos (daniella.santos@ufma.br) on 2017-11-17T18:29:08Z No. of bitstreams: 1 ANTONIOCUNHAFILHO.pdf: 1793440 bytes, checksum: 6416646c9d62d757da9c159657cb5c19 (MD5) / Made available in DSpace on 2017-11-17T18:29:08Z (GMT). No. of bitstreams: 1 ANTONIOCUNHAFILHO.pdf: 1793440 bytes, checksum: 6416646c9d62d757da9c159657cb5c19 (MD5) Previous issue date: 2017-04-28 / CAPES / In the Person with Down Syndrome (DS), autonomic nervous system (ANS) modulation of the heart rhythm can be compromised, resulting in changes in heart rate (HR) and cardiac cycle duration. Capacity to accumulate more adipose tissue is commonly present in people with DS, being this an independent factor for a worse prognosis of sudden death in this population. Objective: To study the effect of physical exercise on autonomic variables and body composition in individuals with active Down Syndrome And sedentary in São Luis-MA. Materials and Methods: This was an analytical and cross-sectional study, data analysis was performed in GraphPad Prism® software, version 5.01 and field research was performed at APAE's in the cities of São Luís - MA. We analyzed 52 individuals with Down Syndrome. Of these individuals, 15 sedentary SD (SDS), 9 SDS (mild active) and 12 SDs (strong active) and 11 controls (CG) were divided through the results obtained in the International Physical Activity Questionnaire (IPAC), anthropometric, hemodynamic and autonomic evaluation in the time domain, frequency domain and symbolic analysis. The constitution in relation to sex was that all were made up of males. Results: SD FH presented lower BMI than Control and SD SD group. Body fat (%) was lower in SED AF / AL than Control and SD group SED. And the hemodynamic parameters were similar between the groups. During the baseline period, there were no significant differences, however, sedentary subjects exhibited lower values in relation to the time domain, such as RR and VAR-RR intervals, when compared to the control group. Frequency domain indexes showed that SD SED individuals had higher values for sympathetic activity regarding low frequency (LF) and similar values for parasympathetic (HF) activity in relation to SD / AF groups. These results, when normalized, presented higher vagal sympathetic balance (LF / HF). In addition, the symbolic analysis showed higher 0V (related to sympathetic activity) and lower values in 2LV (related to parasympathetic activity) in the SD SED group when compared to the control group, SD AL and SD AF. The 2LV was lower in SD-AL and SD AF than in the control group, but 2UV was higher in SD AF than the control group. And there were no differences between the SD / AF group. Conclusion: Thus, we conclude that regardless of intensity, exercise may promote positive adaptations in autonomic modulation in people with Down Syndrome. / No indivíduo com Síndrome de Down (SD), a modulação do sistema nervoso autônomo (SNA) sobre o ritmo cardíaco pode estar comprometida, podendo resultar em alterações na frequência cardíaca (FC) e na duração do ciclo cardíaco. A disfunção do SNA e da capacidade de acumular mais tecido adiposo está comumente presente nas pessoas com SD, sendo este um fator independente para um pior prognóstico de morte súbita nessa população. Objetivo: Analisar o efeito do nível de atividade física nas variáveis autonômicas e composição corporal em indivíduos com Síndrome de Down ativos fortes e leves e sedentários em São Luís-MA. Materiais e Métodos: Trata-se de um estudo do tipo analítico e transversal, a análise dos dados foi realizada no software GraphPad Prism®, versão 5.01 e a pesquisa de campo foi realizada na APAE( Associação de pais e amigos especiais) da cidade da grande São Luís - MA. Foram analisados 52 indivíduos com Síndrome de Down e 11 indivíduos do grupo controle , sem a trissomia 21. Divididos em: 15 grupo SD sedentário (SED), 9 do grupo SD-AL (ativo leve) e 12 do grupo SD-AF (ativo forte) e 11 do grupo Controle (GC) foram divididos através dos resultados obtidos no Questionário Internacional de Atividade Física (IPAC), avaliação antropométrica, hemodinâmica e autonômica no domínio do tempo, domínio de frequência e análise simbólica. Resultados: O SD AF apresentou menor IMC que o Controle e o grupo SD-SED. A gordura corporal (%) foi menor em SED-AF e AL do que o Controle e o grupo SD-SED. Os parâmetros hemodinâmicos foram semelhantes entre os grupos. Durante o período basal, não houve diferenças significativas, contudo, os sujeitos sedentários exibiram valores mais baixos em relação ao domínio do tempo, como intervalos RR e VAR-RR, quando comparados com o grupo controle. Os índices de domínio da frequência mostraram que indivíduos SD-SED valores maiores na atividade simpática referente à baixa frequência (LF) e valores semelhantes na atividade parassimpática (HF) em relação aos grupos SD-AL e AF. Além disso, a análise simbólica mostra maior 0V% (relacionado a atividade simpática) e valores mais baixos em 2LV%(relacionado a atividade parassimpática) no grupo SD SED quando comparado ao grupo controle , SD-AL e SD-AF. O 2LV% foi menor em SD-AL e SD-AF do que o grupo controle, mas 2UV% foi maior em SD-AF do que o grupo controle. E não houve diferenças entre o grupo SD-AL e AF. Conclusão: Independentemente da intensidade, o exercício pode promover adaptações positivas na modulação autonômica em indivíduos com Síndrome de Down.

The Internet consists of thousands of autonomous networks connected together to provide end-to-end reachability. Networks of different sizes, and with different functions and business objectives, interact and co-exist in the evolving "Internet Ecosystem". The Internet ecosystem is highly dynamic, experiencing growth (birth of new networks), rewiring (changes in the connectivity of existing networks), as well as deaths (of existing networks). The dynamics of the Internet ecosystem are determined both by external "environmental" factors (such as the state of the global economy or the popularity of new Internet applications) and the complex incentives and objectives of each network. These dynamics have major implications on how the future Internet will look like. How does the Internet evolve? What is the Internet heading towards, in terms of topological, performance, and economic organization? How do given optimization strategies affect the profitability of different networks? How do these strategies affect the Internet in terms of topology, economics, and performance? In this thesis, we take some steps towards answering the above questions using a combination of measurement and modeling approaches. We first study the evolution of the Autonomous System (AS) topology over the last decade. In particular, we classify ASes and inter-AS links according to their business function, and study separately their evolution over the last 10 years. Next, we focus on enterprise customers and content providers at the edge of the Internet, and propose algorithms for a stub network to choose its upstream providers to maximize its utility (either monetary cost, reliability or performance). Third, we develop a model for interdomain network formation, incorporating the effects of economics, geography, and the provider/peer selections strategies of different types of networks. We use this model to examine the "outcome" of these strategies, in terms of the topology, economics and performance of the resulting internetwork. We also investigate the effect of external factors, such as the nature of the interdomain traffic matrix, customer preferences in provider selection, and pricing/cost structures. Finally, we focus on a recent trend due to the increasing amount of traffic flowing from content providers (who generate content), to access providers (who serve end users). This has led to a tussle between content providers and access providers, who have threatened to prioritize certain types of traffic, or charge content providers directly -- strategies that are viewed as violations of "network neutrality". In our work, we evaluate various pricing and connection strategies that access providers can use to remain profitable without violating network neutrality.

This thesis deals with the decentralized autonomous system, in which individual nodes acting like peers, communicate and participate in collaborative tasks and decision making processes. An experimental test-bed is created using four Garcia robots. The robots act like peers and interact with each other using user datagram protocol (UDP) messages. Each robot continuously monitors for messages coming from other robots and respond accordingly. Each robot broadcasts its location to all the other robots within its vicinity. Robots do not have built-in global positioning system (GPS). So, an indoor localization method based on signal strength is developed to estimate robot's position. The signal strength that the robot gets from the nearby wireless access points is used to calculate the robot's position. Trilateration and fingerprint are some of the indoor localization methods used for this purpose. The communication functionality of the decentralized system has been tested and verified in the autonomous systems laboratory.

This master's thesis describes the hardware and software implementation of autonomous control system for RC toy car. This autonomous car had the task to follow a black line drawn on a white background. Car was enriched with wi-fi for data transfer to computers and the black line is detected by the camera. The main control module was implemented using a single board computer Raspberry Pi.

In connection with the development of autonomous systems supporting artificial intelligence technologies, respectively machine learning, there is a growing concern both in the public and in the media, as well as among legislators and developers. Naturally, such concerns have naturally arisen in the case of other, earlier technologies, but it is clear that there is something atypical in the case of modern technologies. The period when robots, artificial intelligence and other autonomous systems were only a sci-fi topic is already to some extent obsolete and autonomous systems in various forms have been reaching a large number of areas for several years and represent an integral element of the world around us. In practice, more and more companies are engaged in the development of autonomous systems equipped with artificial intelligence, especially the development of chatbots, autonomous vehicles or autonomous drones is nowadays a good example that the operation of similar systems is not so far from reality. In the first and subsequent second chapter, the paper deals in general with an introduction to the topic of autonomous systems with an emphasis on artificial intelligence, respectively machine learning technologies, description of society's ideas of these new technologies, basic defining features...

This thesis presents the integration of an acoustic tracking system within an autonomous underwater AUV (AUV) to enable real-time tracking of sharks tagged with artificial acoustic sources. The tracking system consists of two hydrophones and a receiver unit that outputs a measurement of the relative angle to the tagged shark. Since only two hydrophones are used, the sign of the relative angle measurement is unknown. To overcome this ambiguity, a particle filter algorithm was developed to estimate the position of the acoustic source. When combined with an active control system that drives vehicle to obtain different orientations with respect to the acoustic source, real-time autonomous localization, tracking, and following of a tagged shark is shown to be possible. Four types of ocean experiments were used to validate the system including: 1) AUV tracking of a stationary tag, 2) AUV tracking of a tagged kayak, 3) AUV tracking of a tagged AUV, and 4) AUV tracking of a tagged shark. These experiments were analyzed with respect to the localization error, associated error variance, and distance between the AUV and the tag. The final shark tracking experiments took place in SeaPlane Lagoon, Los Angeles, CA, where the AUV was able to autonomously track and follow a tagged Leopard Shark for several hours.

No description available.