Submitted by Miriam Lucas (miriam.lucas@unioeste.br) on 2018-04-06T14:31:39Z No. of bitstreams: 2 Cristiano_Antonio_de_Souza_2018.pdf: 2020023 bytes, checksum: 1105b369d497031759e007333c20cad9 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-04-06T14:31:39Z (GMT). No. of bitstreams: 2 Cristiano_Antonio_de_Souza_2018.pdf: 2020023 bytes, checksum: 1105b369d497031759e007333c20cad9 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-02-09 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The last decades have been marked by rapid technological development, which was accelerated by the creation of computer networks, and emphatically by the spread and growth of the Internet. As a consequence of this context, private and confidential data of the most diverse areas began to be treated and stored in distributed environments, making vital the security of this data. Due to this fact, the number and variety of attacks on computer systems increased, mainly due to the exploitation of vulnerabilities. Thence, the area of intrusion detection research has gained notoriety, and hybrid detection methods using Artificial Intelligence techniques have been achieving more satisfactory results than the use of such approaches individually. This work consists of a Hybrid method of intrusion detection combining Artificial Neural Network (ANN) and K-Nearest Neighbors KNN techniques. The evaluation of the proposed Hybrid method and the comparison with ANN and KNN techniques individually were developed according to the steps of the Knowledge Discovery in Databases process. For the realization of the experiments, the NSL-KDD public database was selected and, with the attribute selection task, five sub-bases were derived. The experimental results showed that the Hybrid method had better accuracy in relation to ANN in all configurations, whereas in relation to KNN, it reached equivalent accuracy and showed a significant reduction in processing time. Finally, it should be emphasized that among the hybrid configurations evaluated quantitatively and statistically, the best performances in terms of accuracy and classification time were obtained by the hybrid approaches HIB(P25-N75)-C, HIB(P25-N75)-30 and HIB(P25-N75)-20. / As últimas décadas têm sido marcadas pelo rápido desenvolvimento tecnológico, o qual foi acelerado pela criação das redes de computadores, e enfaticamente pela disseminação e crescimento da Internet. Como consequência deste contexto, dados privados e sigilosos das mais diversas áreas passaram a ser tratados e armazenados em ambientes distribuídos, tornando-se vital a segurança dos mesmos. Decorrente ao fato, observa-se um crescimento na quantidade e variedade de ataques a sistemas computacionais, principalmente pela exploração de vulnerabilidades. Em função desse contexto, a área de pesquisa em detecção de intrusão tem ganhado notoriedade, e os métodos híbridos de detecção utilizando técnicas de Inteligência Artificial vêm alcançando resultados mais satisfatórios do que a utilização de tais abordagens de modo individual. Este trabalho consiste em um método Híbrido de detecção de intrusão combinando as técnicas Redes Neurais Artificiais (RNA) e K-Nearest Neighbors (KNN). A avaliação do método Híbrido proposto e a comparação com as técnicas de RNA e KNN isoladamente foram desenvolvidas de acordo com as etapas do processo de Knowledge Discovery in Databases (KDD) . Para a realização dos experimentos selecionou-se a base de dados pública NSL-KDD, sendo que com o processo de seleção de atributos derivou-se cinco sub-bases. Os resultados experimentais comprovaram que o método Híbrido teve melhor acurácia em relação a RNA em todas as configurações, ao passo que em relação ao KNN, alcançou acurácia equivalente e apresentou relevante redução no tempo de processamento. Por fim, cabe ressaltar que dentre as configurações híbridas avaliadas quantitativa e estatisticamente, os melhores desempenhos em termos de acurácia e tempo de classificação foram obtidos pelas abordagens híbridas HIB(P25- N75)-C, HIB(P25-N75)-30 e HIB(P25-N75)-20.

A l'origine conçus pour protéger le protocole de Découverte de Voisins (Neighbor Discovery Protocol, NDP) en IPv6, les adresses générées de manière cryptographique (Cryptographically Generated Addresses, CGA) et le protocole SEND (Secure Neighbor Discovery) doivent maintenant s'adapter au contexte de mobilité et à ses nouvelles fonctionnalités. Cette mobilité revêt de nombreuses formes : mobilité du noeud (Mobile IPv6, MIPv6), mobilité des routeurs (Network Mobility, NEMO) ou encore mobilité gérée par le réseau (Proxy Mobile IPv6). De nombreux changements doivent être opérés dans le protocole SEND : les opérations cryptographiques doivent être allégées pour les terminaux à faible capacité de calcul, les incompatibilités entre le partage d'adresse dans les protocoles de mobilité et le mécanisme de protection d'adresses de SEND doivent être corrigés, etc. Dans une première partie de cette thèse, nous présentons le protocole de Découverte de Voisins, les adresses CGA et le protocole de sécurité SEND. Nous étudions leurs limitations et, afin d'améliorer les performances, nous proposons l'utilisation de la cryptographie basée sur les courbes elliptiques (ECC). À travers une série de tests, nous mesurons l'impact de notre proposition. Par la suite, nous modifions les spécifications du protocole SEND afin de supporter de nouveaux algorithmes crytpographiques. Dans une deuxième partie, nous résolvons les incompatibilités entre le protocole SEND et les protocoles de mobilité (par ex. MIPv6) et entre le protocole SEND et les adresses anycast. Dans une dernière partie, nous présentons plusieurs contributions basées sur une utilisation dérivée des adresses CGA et du protocole SEND. / Originally designed to protect the Neighbor Discovery Protocol (NDP) (part of the IPv6 protocol suite), the Cryptographically Generated Addresses (CGA) and the Secure Neighbor Discovery (SEND) now need to be adapted to the context of Mobility and extended to new functionalities. The term "Mobility" encompasses many aspects, among them : node mobility (Mobile IPv6, MIPv6), router mobility (Network Mobility, NEMO) and network-based mobility management (Proxy Mobile IPv6, PMIPv6). Numerous changes need to be operated on the SEND protocol in order to comply with the Mobility : the cryptographic operations need to be adapted to operate on low power mobile nodes, the incompatibilities between the address sharing model of the mobile protocol and the address protections offered by SEND need to be fixed, etc. Firstly, we present the Neighbor Discovery protocol, the CGA addresses and the SEND protocol. We study their limitations, and, in order to improve their performances, we propose to replace the signature algorithm used in SEND (RSA) by the elliptic curves cryptography (ECC). We then evaluate the performances of our proposal. Subsequently, we modify the SEND protocol to include a signature algorithm selection mechanism. Secondly, we solve incompatilities between the SEND protocol and the mobility protocols (e.g. MIPv6) and between the SEND protocol and the anycast addresses. Finally, we present our contributions containing a derivate use of the CGA addresses and the SEND protocol.

The nearest neighbour problem is of practical significance in a number of fields. Often we are interested in finding an object near to a given query object. The problem is old, and a large number of solutions have been proposed for it in the literature. However, it remains the case that even the most popular of the techniques proposed for its solution have not been compared against each other. Also, many techniques, including the old and popular ones, can be implemented in a number of ways, and often the different implementations of a technique have not been thoroughly compared either. This research presents a detailed investigation of different implementations of two popular nearest neighbour search data structures, KDTrees and Metric Trees, and compares the different implementations of each of the two structures against each other. The best implementations of these structures are then compared against each other and against two other techniques, Annulus Method and Cover Trees. Annulus Method is an old technique that was rediscovered during the research for this thesis. Cover Trees are one of the most novel and promising data structures for nearest neighbour search that have been proposed in the literature.

The conventional Verlet table neighbor list algorithm is improved to reduce the number of unnecessary inter-atomic distance calculations in molecular simulations involving large amount of atoms. Both of the serial and parallelized performance of molecular dynamics simulation are evaluated using the new algorithm and compared with those using the conventional Verlet table and cell-linked list algorithm. Results show that the new algorithm significantly improved the performance of molecular dynamics simulation compared with conventional neighbor list maintaining and utilizing algorithms in serial programs as well as parallelized programs. / Singapore-MIT Alliance (SMA)

Residual vector quantization (RVQ) is a 1-nearest neighbor (1-NN) type of technique. RVQ is a multi-stage implementation of regular vector quantization. An input is successively quantized to the nearest codevector in each stage codebook. In classification, nearest neighbor techniques are very attractive since these techniques very accurately model the ideal Bayes class boundaries. However, nearest neighbor classification techniques require a large size of representative dataset. Since in such techniques a test input is assigned a class membership after an exhaustive search the entire training set, a reasonably large training set can make the implementation cost of the nearest neighbor classifier unfeasibly costly. Although, the k-d tree structure offers a far more efficient implementation of 1-NN search, however, the cost of storing the data points can become prohibitive, especially in higher dimensionality. RVQ also offers a nice solution to a cost-effective implementation of 1-NN-based classification. Because of the direct-sum structure of the RVQ codebook, the memory and computational of cost 1-NN-based system is greatly reduced. Although, as compared to an equivalent 1-NN system, the multi-stage implementation of the RVQ codebook compromises the accuracy of the class boundaries, yet the classification error has been empirically shown to be within 3% to 4% of the performance of an equivalent 1-NN-based classifier.

No description available.

Ägare av webbplatser och applikationer tjänar ofta på att användare klickar på deras länkar. Länkarna kan bland annat vara reklam eller varor som säljs. Det finns många studier inom dataanalys angående om en sådan länk kommer att bli klickad, men få studier fokuserar på hur länkarna kan justeras för att bli klickade. Problemet som företaget Flygresor.se har är att de saknar ett verktyg för deras kunder, resebyråer, att analysera deras biljetter och därefter justera attributen för resorna. Den efterfrågade lösningen var en applikation som gav förslag på hur biljetterna skulle förändras för att bli mer klickade och på såsätt kunna sälja fler resor. I detta arbete byggdes en prototyp som använder sig av två olika datautvinningsmetoder, klustring med algoritmen DBSCAN och klassifikation med algoritmen k-NN. Algoritmerna användes tillsammans med en utvärderingsprocess, kallad DNNA, som analyserade resultatet från dessa två algoritmer och gav förslag på förändringar av artikelns attribut. Kombinationen av algoritmerna tillsammans med DNNA testades och utvärderades som lösning till problemet. Programmet lyckades förutse vilka attribut av biljetter som behövde justeras för att biljetterna skulle bli mer klickade. Rekommendationerna av justeringar var rimliga men eftersom andra liknande verktyg inte hade publicerats kunde detta arbetes resultat inte jämföras. / Owners of websites and applications usually profits through users that clicks on their links. These can be advertisements or items for sale amongst others. There are many studies about data analysis where they tell you if a link will be clicked, but only a few that focus on what needs to be adjusted to get the link clicked. The problem that Flygresor.se have is that they are missing a tool for their customers, travel agencies, that analyses their tickets and after that adjusts the attributes of those trips. The requested solution was an application which gave suggestions about how to change the tickets in a way that would make it more clicked and in that way, make more sales. A prototype was constructed which make use of two different data mining methods, clustering with the algorithm DBSCAN and classification with the algorithm knearest neighbor. These algorithms were used together with an evaluation process, called DNNA, which analyzes the result from the algorithms and gave suggestions about changes that could be done to the attributes of the links. The combination of the algorithms and DNNA was tested and evaluated as the solution to the problem. The program was able to predict what attributes of the tickets needed to be adjusted to get the tickets more clicks. ‘The recommendations of adjustments were reasonable but this result could not be compared to similar tools since they had not been published.

Increasing numbers of people are subscribing to location-based services, but as the popularity grows so are the privacy concerns. Varieties of research exist to address these privacy concerns. Each technique tries to address different models with which location-based services respond to subscribers. In this work, we present ideas to address privacy concerns for the two main models namely: the snapshot nearest neighbor query model and the continuous nearest neighbor query model. First, we address snapshot nearest neighbor query model where location-based services response represents a snapshot of point in time. In this model, we introduce a novel idea based on the concept of an open set in a topological space where points belongs to a subset called neighborhood of a point. We extend this concept to provide anonymity to real objects where each object belongs to a disjointed neighborhood such that each neighborhood contains a single object. To help identify the objects, we implement a database which dynamically scales in direct proportion with the size of the neighborhood. To retrieve information secretly and allow the database to expose only requested information, private information retrieval protocols are executed twice on the data. Our study of the implementation shows that the concept of a single object neighborhood is able to efficiently scale the database with the objects in the area. The size of the database grows with the size of the grid and the objects covered by the location-based services. Typically, creating neighborhoods, computing distances between objects in the area, and running private information retrieval protocols causes the CPU to respond slowly with this increase in database size. In order to handle a large number of objects, we explore the concept of kernel and parallel computing in GPU. We develop GPU parallel implementation of the snapshot query to handle large number of objects. In our experiment, we exploit parameter tuning. The results show that with parameter tuning and parallel computing power of GPU we are able to significantly reduce the response time as the number of objects increases. To determine response time of an application without knowledge of the intricacies of GPU architecture, we extend our analysis to predict GPU execution time. We develop the run time equation for an operation and extrapolate the run time for a problem set based on the equation, and then we provide a model to predict GPU response time. As an alternative, the snapshot nearest neighbor query privacy problem can be addressed using secure hardware computing which can eliminate the need for protecting the rest of the sub-system, minimize resource usage and network transmission time. In this approach, a secure coprocessor is used to provide privacy. We process all information inside the coprocessor to deny adversaries access to any private information. To obfuscate access pattern to external memory location, we use oblivious random access memory methodology to access the server. Experimental evaluation shows that using a secure coprocessor reduces resource usage and query response time as the size of the coverage area and objects increases. Second, we address privacy concerns in the continuous nearest neighbor query model where location-based services automatically respond to a change in object*s location. In this model, we present solutions for two different types known as moving query static object and moving query moving object. For the solutions, we propose plane partition using a Voronoi diagram, and a continuous fractal space filling curve using a Hilbert curve order to create a continuous nearest neighbor relationship between the points of interest in a path. Specifically, space filling curve results in multi-dimensional to 1-dimensional object mapping where values are assigned to the objects based on proximity. To prevent subscribers from issuing a query each time there is a change in location and to reduce the response time, we introduce the concept of transition and update time to indicate where and when the nearest neighbor changes. We also introduce a database that dynamically scales with the size of the objects in a path to help obscure and relate objects. By executing the private information retrieval protocol twice on the data, the user secretly retrieves requested information from the database. The results of our experiment show that using plane partitioning and a fractal space filling curve to create nearest neighbor relationships with transition time between objects reduces the total response time.

The prospect of replacing existing fixed networks with cheap, flexible and evenmobile low-power wireless network has been a strong research driver in recent years.However, many challenges still exist: reliability is hampered by unstable and burstycommunication links; the wireless medium is getting congested by an increasingnumber of wireless devices; and life-times are limited due to difficulties in developingefficient duty-cycling mechanisms. These challenges inhibit the industry to fullyembrace and exploit the capabilities and business opportunities that low-powerwireless devices offer. In this thesis, we propose, design, implement, and evaluateprotocols and systems to increase flexibility and improve efficiency of low-powerwireless communications. First, we present MobiSense, a system architecture for energy-efficient communicationsin micro-mobility sensing scenarios. MobiSense is a hybrid architecturecombining a fixed infrastructure network and mobile sensor nodes. Simulations andexperimental results show that the system provides high throughput and reliabilitywith low-latency handoffs. Secondly, we investigate if and how multi-channel communication can mitigate theimpact of link dynamics on low-power wireless protocols. Our study is motivated bya curiosity to reconcile two opposing views: that link dynamics is best compensatedby either (i) adaptive routing, or (ii) multi-channel communication. We perform acomprehensive measurement campaign and evaluate performance both in the singlelink and over a multi-hop network. We study packet reception ratios, maximumburst losses, temporal correlation of losses and loss correlations across channels.The evaluation shows that multi-channel communication significantly reduces linkburstiness and packet losses. In multi-hop networks, multi-channel communicationsand adaptive routing achieves similar end-to-end reliability in dense topologies,while multi-channel communication outperforms adaptive routing in sparse networkswhere re-routing options are limited. Third, we address the problem of distributed information exchange in proximitybasednetworks. First, we consider randomized information exchange and assess thepotential of multi-channel epidemic discovery. We propose an epidemic neightbordiscoverymechanism that reduces discovery times considerably compared to singlechannelprotocols in large and dense networks. Then, the idea is extended todeterministic information exchange. We propose, design and evaluate an epidemicinformation dissemination mechanism with strong performance both in theory andpractice. Finally, we apply some of the concepts from epidemic discovery to the designof an asynchronous, sender-initiated multi-channel medium access protocol. Theprotocol combines a novel mechanism for rapid schedule learning that avoids perpacketchannel negotiations with the use of burst data transfer to provide efficientsupport of ’multiple contending unicast and parallel data flows. / De senaste åren har forskning inom trådlös kommunikation drivits av önskemåletom att kunna ersätta nuvarande trådbundna kommunikationslänkar med trådlösa lågenergialternativ.Dock kvarstår många utmaningar, såsom instabila och sporadiskalänkar, överbelastning på grund av en ökning i antal trådlösa enheter, hur maneffektivt kan växla duty-cycling mekanismen för att förlänga nätverkens livstid,med flera. Dessa utmaningar begränsar industrin från att ta till sig och utnyttjade fördelar som trådlösa lågenergialternativ kan medföra. I den här avhandlingenföreslår, designar, implementerar och utvärderar vi protokoll och system som kanförbättra de nuvarande trådlösa lågenergialternativen. Först presenterar vi MobiSense, en systemarkitektur för energibesparande kommunikationi mikro-mobila sensorscenarier. MobiSense är en hybridarkitektur somkombinerar ett fast infrastrukturnätverk med rörliga sensornoder. Simulerings- ochexperimentella resultat visar att systemet uppnår en högre överföringskapacitet ochtillförlitlighet samtidigt som överlämnandet mellan basstationer har låg latens. I den andra delen behandlar vi hur effekterna från länkdynamiken hos protokollför lågenergikommunikation kan minskas, och försöker förena idéerna hos två motståendesynsätt: (i) flerkanalskommunikation och (ii) adaptiv routing. Vi analyserarenkanals- och flerkanalskommunikation över en-stegslänkar i termer av andelenmottagna paket kontra andelen förlorade, den maximala sporadiska förlusten avpaket, tidskorrelation för förluster och förlustkorrelation mellan olika kanaler. Resultatenindikerar att flerkanalskommunikation med kanalhoppning kraftigt minskardet sporadiska uppträdandet hos länkarna och korrelationen mellan paketförluster.För flerstegsnätverk uppvisar flerkanalskommunikation och adaptiv routingliknande tillförlitlighet i täta topologier, medan flerkanalskommunikation har bättreprestanda än adaptiv routing i glesa nätverk med sporadiska länkar. I den tredje delen studeras distribuerat informationsutbyte i närhetsbaseradenätverk. Först betraktas det slumpmässiga fallet och vi fastställer potentialen hosflerkanalig indirekt utforskning av nätverket. Vi analyserar ett trestegs protokoll,som möjliggör en snabbare utforskning av nätverket. Sedan föreslår vi en ny algoritmför att upptäcka grannarna i ett flerkanalsnätverk, som kraftigt minskarutforskningstiden i jämförelse med ett enkanalsprotokoll. Vi utökar även problemettill det deterministiska fallet och föreslår en mekanism för informationsspridningsom påskyndar utforskningstiderna för deterministiska protokoll. Utvidgningen hartvå huvudförbättringar som leder till kraftigt ökad prestanda samtidigt som degaranterar att utforskningsprocessen är deterministisk. Till sist applicerar vi koncepten rörande indirekt utforskning för att designa,implementera och evaluera ett asynkront sändare-initierat flerkanals MAC protokollför trådlös lågenergikommunikation. Protokollet kombinerar en ny mekanism försnabbt lärande av tidsschemat, vilket undviker kanalförhandling för varje paket,med sporadisk dataöverföring. Detta möjliggör ett effektivt tillhandahållande avflera konkurrerande och parallella dataflöden. / <p>QC 20151204</p>

This thesis attempts to demonstrate how Reverend and Professor Hubert Herring’s dedication to Congregationalism motivated him to advocate for the autonomy of Latin American nations through the pursuit of non-interventionist policies, an approach the U.S. government ultimately adopted when it best suited its interests during World War II.