Characterizing the IoT ecosystem at scale

Internet of Things (IoT) devices are extremely popular with home, business, and industrial users. To provide their services, they typically rely on a backend server in- frastructure on the Internet, which collectively form the IoT Ecosystem. This ecosys- tem is rapidly growing and offers users an increasing number of services. It also has been a source and target of significant security and privacy risks. One notable exam- ple is the recent large-scale coordinated global attacks, like Mirai, which disrupted large service providers. Thus, characterizing this ecosystem yields insights that help end-users, network operators, policymakers, and researchers better understand it, obtain a detailed view, and keep track of its evolution. In addition, they can use these insights to inform their decision-making process for mitigating this ecosystem’s security and privacy risks. In this dissertation, we characterize the IoT ecosystem at scale by (i) detecting the IoT devices in the wild, (ii) conducting a case study to measure how deployed IoT devices can affect users’ privacy, and (iii) detecting and measuring the IoT backend infrastructure. To conduct our studies, we collaborated with a large European Internet Service Provider (ISP) and a major European Internet eXchange Point (IXP). They rou- tinely collect large volumes of passive, sampled data, e.g., NetFlow and IPFIX, for their operational purposes. These data sources help providers obtain insights about their networks, and we used them to characterize the IoT ecosystem at scale. We start with IoT devices and study how to track and trace their activity in the wild. We developed and evaluated a scalable methodology to accurately detect and monitor IoT devices with limited, sparsely sampled data in the ISP and IXP. Next, we conduct a case study to measure how a myriad of deployed devices can affect the privacy of ISP subscribers. Unfortunately, we found that the privacy of a substantial fraction of IPv6 end-users is at risk. We noticed that a single device at home that encodes its MAC address into the IPv6 address could be utilized as a tracking identifier for the entire end-user prefix—even if other devices use IPv6 privacy extensions. Our results showed that IoT devices contribute the most to this privacy leakage. Finally, we focus on the backend server infrastructure and propose a methodology to identify and locate IoT backend servers operated by cloud services and IoT vendors. We analyzed their IoT traffic patterns as observed in the ISP. Our analysis sheds light on their diverse operational and deployment strategies. The need for issuing a priori unknown network-wide queries against large volumes of network flow capture data, which we used in our studies, motivated us to develop Flowyager. It is a system built on top of existing traffic capture utilities, and it relies on flow summarization techniques to reduce (i) the storage and transfer cost of flow captures and (ii) query response time. We deployed a prototype of Flowyager at both the IXP and ISP.Internet-of-Things-Geräte (IoT) sind aus vielen Haushalten, Büroräumen und In- dustrieanlagen nicht mehr wegzudenken. Um ihre Dienste zu erbringen, nutzen IoT- Geräte typischerweise auf eine Backend-Server-Infrastruktur im Internet, welche als Gesamtheit das IoT-Ökosystem bildet. Dieses Ökosystem wächst rapide an und bie- tet den Nutzern immer mehr Dienste an. Das IoT-Ökosystem ist jedoch sowohl eine Quelle als auch ein Ziel von signifikanten Risiken für die Sicherheit und Privatsphäre. Ein bemerkenswertes Beispiel sind die jüngsten groß angelegten, koordinierten globa- len Angriffe wie Mirai, durch die große Diensteanbieter gestört haben. Deshalb ist es wichtig, dieses Ökosystem zu charakterisieren, eine ganzheitliche Sicht zu bekommen und die Entwicklung zu verfolgen, damit Forscher, Entscheidungsträger, Endnutzer und Netzwerkbetreibern Einblicke und ein besseres Verständnis erlangen. Außerdem können alle Teilnehmer des Ökosystems diese Erkenntnisse nutzen, um ihre Entschei- dungsprozesse zur Verhinderung von Sicherheits- und Privatsphärerisiken zu verbes- sern. In dieser Dissertation charakterisieren wir die Gesamtheit des IoT-Ökosystems indem wir (i) IoT-Geräte im Internet detektieren, (ii) eine Fallstudie zum Einfluss von benutzten IoT-Geräten auf die Privatsphäre von Nutzern durchführen und (iii) die IoT-Backend-Infrastruktur aufdecken und vermessen. Um unsere Studien durchzuführen, arbeiten wir mit einem großen europäischen Internet- Service-Provider (ISP) und einem großen europäischen Internet-Exchange-Point (IXP) zusammen. Diese sammeln routinemäßig für operative Zwecke große Mengen an pas- siven gesampelten Daten (z.B. als NetFlow oder IPFIX). Diese Datenquellen helfen Netzwerkbetreibern Einblicke in ihre Netzwerke zu erlangen und wir verwendeten sie, um das IoT-Ökosystem ganzheitlich zu charakterisieren. Wir beginnen unsere Analysen mit IoT-Geräten und untersuchen, wie diese im Inter- net aufgespürt und verfolgt werden können. Dazu entwickelten und evaluierten wir eine skalierbare Methodik, um IoT-Geräte mit Hilfe von eingeschränkten gesampelten Daten des ISPs und IXPs präzise erkennen und beobachten können. Als Nächstes führen wir eine Fallstudie durch, in der wir messen, wie eine Unzahl von eingesetzten Geräten die Privatsphäre von ISP-Nutzern beeinflussen kann. Lei- der fanden wir heraus, dass die Privatsphäre eines substantiellen Teils von IPv6- Endnutzern bedroht ist. Wir entdeckten, dass bereits ein einzelnes Gerät im Haus, welches seine MAC-Adresse in die IPv6-Adresse kodiert, als Tracking-Identifikator für das gesamte Endnutzer-Präfix missbraucht werden kann — auch wenn andere Geräte IPv6-Privacy-Extensions verwenden. Unsere Ergebnisse zeigten, dass IoT-Geräte den Großteil dieses Privatsphäre-Verlusts verursachen. Abschließend fokussieren wir uns auf die Backend-Server-Infrastruktur und wir schla- gen eine Methodik zur Identifizierung und Lokalisierung von IoT-Backend-Servern vor, welche von Cloud-Diensten und IoT-Herstellern betrieben wird. Wir analysier- ten Muster im IoT-Verkehr, der vom ISP beobachtet wird. Unsere Analyse gibt Auf- schluss über die unterschiedlichen Strategien, wie IoT-Backend-Server betrieben und eingesetzt werden. Die Notwendigkeit a-priori unbekannte netzwerkweite Anfragen an große Mengen von Netzwerk-Flow-Daten zu stellen, welche wir in in unseren Studien verwenden, moti- vierte uns zur Entwicklung von Flowyager. Dies ist ein auf bestehenden Netzwerkverkehrs- Tools aufbauendes System und es stützt sich auf die Zusammenfassung von Verkehrs- flüssen, um (i) die Kosten für Archivierung und Transfer von Flow-Daten und (ii) die Antwortzeit von Anfragen zu reduzieren. Wir setzten einen Prototypen von Flowyager sowohl im IXP als auch im ISP ein

Detection and Mitigation of Steganographic Malware

A new attack trend concerns the use of some form of steganography and information hiding to make malware stealthier and able to elude many standard security mechanisms. Therefore, this Thesis addresses the detection and the mitigation of this class of threats. In particular, it considers malware implementing covert communications within network traffic or cloaking malicious payloads within digital images. The first research contribution of this Thesis is in the detection of network covert channels. Unfortunately, the literature on the topic lacks of real traffic traces or attack samples to perform precise tests or security assessments. Thus, a propaedeutic research activity has been devoted to develop two ad-hoc tools. The first allows to create covert channels targeting the IPv6 protocol by eavesdropping flows, whereas the second allows to embed secret data within arbitrary traffic traces that can be replayed to perform investigations in realistic conditions. This Thesis then starts with a security assessment concerning the impact of hidden network communications in production-quality scenarios. Results have been obtained by considering channels cloaking data in the most popular protocols (e.g., TLS, IPv4/v6, and ICMPv4/v6) and showcased that de-facto standard intrusion detection systems and firewalls (i.e., Snort, Suricata, and Zeek) are unable to spot this class of hazards. Since malware can conceal information (e.g., commands and configuration files) in almost every protocol, traffic feature or network element, configuring or adapting pre-existent security solutions could be not straightforward. Moreover, inspecting multiple protocols, fields or conversations at the same time could lead to performance issues. Thus, a major effort has been devoted to develop a suite based on the extended Berkeley Packet Filter (eBPF) to gain visibility over different network protocols/components and to efficiently collect various performance indicators or statistics by using a unique technology. This part of research allowed to spot the presence of network covert channels targeting the header of the IPv6 protocol or the inter-packet time of generic network conversations. In addition, the approach based on eBPF turned out to be very flexible and also allowed to reveal hidden data transfers between two processes co-located within the same host. Another important contribution of this part of the Thesis concerns the deployment of the suite in realistic scenarios and its comparison with other similar tools. Specifically, a thorough performance evaluation demonstrated that eBPF can be used to inspect traffic and reveal the presence of covert communications also when in the presence of high loads, e.g., it can sustain rates up to 3 Gbit/s with commodity hardware. To further address the problem of revealing network covert channels in realistic environments, this Thesis also investigates malware targeting traffic generated by Internet of Things devices. In this case, an incremental ensemble of autoencoders has been considered to face the ''unknown'' location of the hidden data generated by a threat covertly exchanging commands towards a remote attacker. The second research contribution of this Thesis is in the detection of malicious payloads hidden within digital images. In fact, the majority of real-world malware exploits hiding methods based on Least Significant Bit steganography and some of its variants, such as the Invoke-PSImage mechanism. Therefore, a relevant amount of research has been done to detect the presence of hidden data and classify the payload (e.g., malicious PowerShell scripts or PHP fragments). To this aim, mechanisms leveraging Deep Neural Networks (DNNs) proved to be flexible and effective since they can learn by combining raw low-level data and can be updated or retrained to consider unseen payloads or images with different features. To take into account realistic threat models, this Thesis studies malware targeting different types of images (i.e., favicons and icons) and various payloads (e.g., URLs and Ethereum addresses, as well as webshells). Obtained results showcased that DNNs can be considered a valid tool for spotting the presence of hidden contents since their detection accuracy is always above 90% also when facing ''elusion'' mechanisms such as basic obfuscation techniques or alternative encoding schemes. Lastly, when detection or classification are not possible (e.g., due to resource constraints), approaches enforcing ''sanitization'' can be applied. Thus, this Thesis also considers autoencoders able to disrupt hidden malicious contents without degrading the quality of the image

Network traffic management for the next generation Internet

Measurement-based performance evaluation of network traffic is a fundamental prerequisite for the provisioning of managed and controlled services in short timescales, as well as for enabling the accountability of network resources. The steady introduction and deployment of the Internet Protocol Next Generation (IPNG-IPv6) promises a network address space that can accommodate any device capable of generating a digital heart-beat. Under such a ubiquitous communication environment, Internet traffic measurement becomes of particular importance, especially for the assured provisioning of differentiated levels of service quality to the different application flows. The non-identical response of flows to the different types of network-imposed performance degradation and the foreseeable expansion of networked devices raise the need for ubiquitous measurement mechanisms that can be equally applicable to different applications and transports. This thesis introduces a new measurement technique that exploits native features of IPv6 to become an integral part of the Internet's operation, and to provide intrinsic support for performance measurements at the universally-present network layer. IPv6 Extension Headers have been used to carry both the triggers that invoke the measurement activity and the instantaneous measurement indicators in-line with the payload data itself, providing a high level of confidence that the behaviour of the real user traffic flows is observed. The in-line measurements mechanism has been critically compared and contrasted to existing measurement techniques, and its design and a software-based prototype implementation have been documented. The developed system has been used to provisionally evaluate numerous performance properties of a diverse set of application flows, over different-capacity IPv6 experimental configurations. Through experimentation and theoretical argumentation, it has been shown that IPv6-based, in-line measurements can form the basis for accurate and low-overhead performance assessment of network traffic flows in short time-scales, by being dynamically deployed where and when required in a multi-service Internet environment.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

TOWARD AUTOMATED THREAT MODELING BY ADVERSARY NETWORK INFRASTRUCTURE DISCOVERY

Threat modeling can help defenders ascertain potential attacker capabilities and resources, allowing better protection of critical networks and systems from sophisticated cyber-attacks. One aspect of the adversary profile that is of interest to defenders is the means to conduct a cyber-attack, including malware capabilities and network infrastructure. Even though most defenders collect data on cyber incidents, extracting knowledge about adversaries to build and improve the threat model can be time-consuming. This thesis applies machine learning methods to historical cyber incident data to enable automated threat modeling of adversary network infrastructure. Using network data of attacker command and control servers based on real-world cyber incidents, specific adversary datasets can be created and enriched using the capabilities of internet-scanning search engines. Mixing these datasets with data from benign or non-associated hosts with similar port-service mappings allows for building an interpretable machine learning model of attackers. Additionally, creating internet-scanning search engine queries based on machine learning model predictions allows for automating threat modeling of adversary infrastructure. Automated threat modeling of adversary network infrastructure allows searching for unknown or emerging threat actor network infrastructure on the Internet.Major, Ukrainian Ground ForcesApproved for public release. Distribution is unlimited

BGP-Multipath Routing in the Internet

BGP-Multipath, or BGP-M, is a routing technique for balancing traffic load in the Internet. It enables a Border Gateway Protocol (BGP) border router to install multiple ‘equally-good’ paths to a destination prefix. While other multipath routing techniques are deployed at internal routers, BGP-M is deployed at border routers where traffic is shared on multiple border links between Autonomous Systems (ASes). Although there are a considerable number of research efforts on multipath routing, there is so far no dedicated measurement or study on BGP-M in the literature. This thesis presents the first systematic study on BGP-M. I proposed a novel approach to inferring the deployment of BGP-M by querying Looking Glass (LG) servers. I conducted a detailed investigation on the deployment of BGP-M in the Internet. I also analysed BGP-M’s routing properties based on traceroute measurements using RIPE Atlas probes. My research has revealed that BGP-M has already been used in the Internet. In particular, Hurricane Electric (AS6939), a Tier-1 network operator, has deployed BGP-M at border routers across its global network to hundreds of its neighbour ASes on both IPv4 and IPv6 Internet. My research has provided the state-of-the-art knowledge and insights in the deployment, configuration and operation of BGP-M. The data, methods and analysis introduced in this thesis can be immensely valuable to researchers, network operators and regulators who are interested in improving the performance and security of Internet routing. This work has raised awareness of BGP-M and may promote more deployment of BGP-M in future because BGP-M not only provides all benefits of multipath routing but also has distinct advantages in terms of flexibility, compatibility and transparency

Adaptation of the human nervous system for self-aware secure mobile and IoT systems

IT systems have been deployed across several domains, such as hospitals and industries, for the management of information and operations. These systems will soon be ubiquitous in every field due to the transition towards the Internet of Things (IoT). The IoT brings devices with sensory functions into IT systems through the process of internetworking. The sensory functions of IoT enable them to generate and process information automatically, either without human contribution or having the least human interaction possible aside from the information and operations management tasks. Security is crucial as it prevents system exploitation. Security has been employed after system implementation, and has rarely been considered as a part of the system. In this dissertation, a novel solution based on a biological approach is presented to embed security as an inalienable part of the system. The proposed solution, in the form of a prototype of the system, is based on the functions of the human nervous system (HNS) in protecting its host from the impacts caused by external or internal changes. The contributions of this work are the derivation of a new system architecture from HNS functionalities and experiments that prove the implementation feasibility and efficiency of the proposed HNS-based architecture through prototype development and evaluation. The first contribution of this work is the adaptation of human nervous system functions to propose a new architecture for IT systems security. The major organs and functions of the HNS are investigated and critical areas are identified for the adaptation process. Several individual system components with similar functions to the HNS are created and grouped to form individual subsystems. The relationship between these components is established in a similar way as in the HNS, resulting in a new system architecture that includes security as a core component. The adapted HNS-based system architecture is employed in two the experiments prove its implementation capability, enhancement of security, and overall system operations. The second contribution is the implementation of the proposed HNS-based security solution in the IoT test-bed. A temperature-monitoring application with an intrusion detection system (IDS) based on the proposed HNS architecture is implemented as part of the test-bed experiment. Contiki OS is used for implementation, and the 6LoWPAN stack is modified during the development process. The application, together with the IDS, has a brain subsystem (BrSS), a spinal cord subsystem (SCSS), and other functions similar to the HNS whose names are changed. The HNS functions are shared between an edge router and resource-constrained devices (RCDs) during implementation. The experiment is evaluated in both test-bed and simulation environments. Zolertia Z1 nodes are used to form a 6LoWPAN network, and an edge router is created by combining Pandaboard and Z1 node for a test-bed setup. Two networks with different numbers of sensor nodes are used as simulation environments in the Cooja simulator. The third contribution of this dissertation is the implementation of the proposed HNS-based architecture in the mobile platform. In this phase, the Android operating system (OS) is selected for experimentation, and the proposed HNS-based architecture is specifically tailored for Android. A context-based dynamically reconfigurable access control system (CoDRA) is developed based on the principles of the refined HNS architecture. CoDRA is implemented through customization of Android OS and evaluated under real-time usage conditions in test-bed environments. During the evaluation, the implemented prototype mimicked the nature of the HNS in securing the application under threat with negligible resource requirements and solved the problems in existing approaches by embedding security within the system. Furthermore, the results of the experiments highlighted the retention of HNS functions after refinement for different IT application areas, especially the IoT, due to its resource-constrained nature, and the implementable capability of our proposed HNS architecture.--- IT-järjestelmiä hyödynnetään tiedon ja toimintojen hallinnassa useilla aloilla, kuten sairaaloissa ja teollisuudessa. Siirtyminen kohti esineiden Internetiä (Internet of Things, IoT) tuo tällaiset laitteet yhä kiinteämmäksi osaksi jokapäiväistä elämää. IT-järjestelmiin liitettyjen IoT-laitteiden sensoritoiminnot mahdollistavat tiedon automaattisen havainnoinnin ja käsittelyn osana suurempaa järjestelmää jopa täysin ilman ihmisen myötävaikutusta, poislukien mahdolliset ylläpito- ja hallintatoimenpiteet. Turvallisuus on ratkaisevan tärkeää IT-järjestelmien luvattoman käytön estämiseksi. Valitettavan usein järjestelmäsuunnittelussa turvallisuus ei ole osana ydinsuunnitteluprosessia, vaan otetaan huomioon vasta käyttöönoton jälkeen. Tässä väitöskirjassa esitellään uudenlainen biologiseen lähestymistapaan perustuva ratkaisu, jolla turvallisuus voidaan sisällyttää erottamattomaksi osaksi järjestelmää. Ehdotettu prototyyppiratkaisu perustuu ihmisen hermoston toimintaan tilanteessa, jossa se suojelee isäntäänsä ulkoisten tai sisäisten muutosten vaikutuksilta. Tämän työn keskeiset tulokset ovat uuden järjestelmäarkkitehtuurin johtaminen ihmisen hermoston toimintaperiaatteesta sekä tällaisen järjestelmän toteutettavuuden ja tehokkuuden arviointi kokeellisen prototyypin kehittämisen ja toiminnan arvioinnin avulla. Tämän väitöskirjan ensimmäinen kontribuutio on ihmisen hermoston toimintoihin perustuva IT-järjestelmäarkkitehtuuri. Tutkimuksessa arvioidaan ihmisen hermoston toimintaa ja tunnistetaan keskeiset toiminnot ja toiminnallisuudet, jotka mall-innetaan osaksi kehitettävää järjestelmää luomalla näitä vastaavat järjestelmäkomponentit. Nä-istä kootaan toiminnallisuudeltaan hermostoa vastaavat osajärjestelmät, joiden keskinäinen toiminta mallintaa ihmisen hermoston toimintaa. Näin luodaan arkkitehtuuri, jonka keskeisenä komponenttina on turvallisuus. Tämän pohjalta toteutetaan kaksi prototyyppijärjestelmää, joiden avulla arvioidaan arkkitehtuurin toteutuskelpoisuutta, turvallisuutta sekä toimintakykyä. Toinen kontribuutio on esitetyn hermostopohjaisen turvallisuusratkaisun toteuttaminen IoT-testialustalla. Kehitettyyn arkkitehtuuriin perustuva ja tunkeutumisen estojärjestelmän (intrusion detection system, IDS) sisältävä lämpötilan seurantasovellus toteutetaan käyttäen Contiki OS -käytöjärjestelmää. 6LoWPAN protokollapinoa muokataan tarpeen mukaan kehitysprosessin aikana. IDS:n lisäksi sovellukseen kuuluu aivo-osajärjestelmä (Brain subsystem, BrSS), selkäydinosajärjestelmä (Spinal cord subsystem, SCSS), sekä muita hermoston kaltaisia toimintoja. Nämä toiminnot jaetaan reunareitittimen ja resurssirajoitteisten laitteiden kesken. Tuloksia arvioidaan sekä simulaatioiden että testialustan tulosten perusteella. Testialustaa varten 6LoWPAN verkon toteutukseen valittiin Zolertia Z1 ja reunareititin on toteutettu Pandaboardin ja Z1:n yhdistelmällä. Cooja-simulaattorissa käytettiin mallinnukseen ymp-äristönä kahta erillistä ja erikokoisuta sensoriverkkoa. Kolmas tämän väitöskirjan kontribuutio on kehitetyn hermostopohjaisen arkkitehtuurin toteuttaminen mobiilialustassa. Toteutuksen alustaksi valitaan Android-käyttöjärjestelmä, ja kehitetty arkkitehtuuri räätälöidään Androidille. Tuloksena on kontekstipohjainen dynaamisesti uudelleen konfiguroitava pääsynvalvontajärjestelmä (context-based dynamically reconfigurable access control system, CoDRA). CoDRA toteutetaan mukauttamalla Androidin käyttöjärjestelmää ja toteutuksen toimivuutta arvioidaan reaaliaikaisissa käyttöolosuhteissa testialustaympäristöissä. Toteutusta arvioitaessa havaittiin, että kehitetty prototyyppi jäljitteli ihmishermoston toimintaa kohdesovelluksen suojaamisessa, suoriutui tehtävästään vähäisillä resurssivaatimuksilla ja onnistui sisällyttämään turvallisuuden järjestelmän ydintoimintoihin. Tulokset osoittivat, että tämän tyyppinen järjestelmä on toteutettavissa sekä sen, että järjestelmän hermostonkaltainen toiminnallisuus säilyy siirryttäessä sovellusalueelta toiselle, erityisesti resursseiltaan rajoittuneissa IoT-järjestelmissä

A Survey on Virtualization of Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization

A system for the detection of limited visibility in BGP

Mención Internacional en el título de doctorThe performance of the global routing system is vital to thousands of entities operating the Autonomous Systems (ASes) which make up the Internet. The Border Gateway Protocol (BGP) is currently responsible for the exchange of reachability information and the selection of paths according to their specified routing policies. BGP thus enables traffic to flow from any point to another connected to the Internet. The manner traffic flows if often influenced by entities in the Internet according to their preferences. The latter are implemented in the form of routing policies by tweaking BGP configurations. Routing policies are usually complex and aim to achieve a myriad goals, including technical, economic and political purposes. Additionally, individual network managers need to permanently adapt to the interdomain routing changes and, by engineering the Internet traffic, optimize the use of their network. Despite the flexibility offered, the implementation of routing policies is a complicated process in itself, involving fine-tuning operations. Thus, it is an error-prone task and operators might end up with faulty configurations that impact the efficacy of their strategies or, more importantly, their revenues. Withal, even when correctly defining legitimate routing policies, unforeseen interactions between ASes have been observed to cause important disruptions that affect the global routing system. The main reason behind this resides in the fact that the actual inter-domain routing is the result of the interplay of many routing policies from ASes across the Internet, possibly bringing about a different outcome than the one expected. In this thesis, we perform an extensive analysis of the intricacies emerging from the complex netting of routing policies at the interdomain level, in the context of the current operational status of the Internet. Abundant implications on the way traffic flows in the Internet arise from the convolution of routing policies at a global scale, at times resulting in ASes using suboptimal ill-favored paths or in the undetected propagation of configuration errors in routing system. We argue here that monitoring prefix visibility at the interdomain level can be used to detect cases of faulty configurations or backfired routing policies, which disrupt the functionality of the routing system. We show that the lack of global prefix visibility can offer early warning signs for anomalous events which, despite their impact, often remain hidden from state of the art tools. Additionally, we show that such unintended Internet behavior not only degrades the efficacy of the routing policies implemented by operators, causing their traffic to follow ill-favored paths, but can also point out problems in the global connectivity of prefixes. We further observe that majority of prefixes suffering from limited visibility at the interdomain level is a set of more-specific prefixes, often used by network operators to fulfill binding traffic engineering needs. One important task achieved through the use of routing policies for traffic engineering is the control and optimization of the routing function in order to allow the ASes to engineer the incoming traffic. The advertisement of more-specific prefixes, also known as prefix deaggregation, provides network operators with a fine-grained method to control the interdomain ingress traffic, given that the longest-prefix match rule over-rides any other routing policy applied to the covering lessspecific prefixes. Nevertheless, however efficient, this traffic engineering tool comes with a cost, which is usually externalized to the entire Internet community. Prefix deaggregation is a known reason for the artificial inflation of the BGP routing table, which can further affect the scalability of the global routing system. Looking past the main motivation for deploying deaggregation in the first place, we identify and analyze here the economic impact of this type of strategy. We propose a general Internet model to analyze the effect that advertising more-specific prefixes has on the incoming transit traffic burstiness. We show that deaggregation combined with selective advertisements (further defined as strategic deaggregation) has a traffic stabilization side-effect, which translates into a decrease of the transit traffic bill. Next, we develop a methodology for Internet Service Providers (ISPs) to monitor general occurrences of deaggregation within their customer base. Furthermore, the ISPs can detect selective advertisements of deaggregated prefixes, and thus identify customers which may impact the business of their providers. We apply the proposed methodology on a complete set of data including routing, traffic, topological and billing information provided by an operational ISP and we discuss the obtained results.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Arturo Azcorra Saloña.- Secretario: Steffano Vissichio.- Vocal: Kc. Claff

Virtual Mobility Domains - A Mobility Architecture for the Future Internet

The advances in hardware and wireless technologies have made mobile communication devices affordable by a vast user community. With the advent of rich multimedia and social networking content, an influx of myriads of applications, and Internet supported services, there is an increasing user demand for the Internet connectivity anywhere and anytime. Mobility management is thus a crucial requirement for the Internet today. This work targets novel mobility management techniques, designed to work with the Floating Cloud Tiered (FCT) internetworking model, proposed for a future Internet. We derive the FCT internetworking model from the tiered structure existing among Internet Service Provider (ISP) networks, to define their business and peering relationships. In our novel mobility management scheme, we define Virtual Mobility Domains (VMDs) of various scopes, that can support both intra and inter-domain roaming using a single address for a mobile node. The scheme is network based and hence imposes no operational load on the mobile node. This scheme is the first of its kind, by leveraging the tiered structure and its hierarchical properties, the collaborative network-based mobility management mechanism, and the inheritance information in the tiered addresses to route packets. The contributions of this PhD thesis can be summarized as follows: · We contribute to the literature with a comprehensive analysis of the future Internet architectures and mobility protocols over the period of 2002-2012, in light of their identity and handoff management schemes. We present a qualitative evaluation of current and future schemes on a unified platform. · We design and implement a novel user-centric future Internet mobility architecture called Virtual Mobility Domain. VMD proposes a seamless, network-based, unique collaborative mobility management within/across ASes and ISPs in the FCT Internetworking model. The analytical and simulation-based handoff performance analysis of the VMD architecture in comparison with the IPv6-based mobility protocols presents the considerable performance improvements achieved by the VMD architecture. · We present a novel and user-centric handoff cost framework to analyze handoff performance of different mobility schemes. The framework helps to examine the impacts of registration costs, signaling overhead, and data loss for Internet connected mobile users employing a unified cost metric. We analyze the effect of each parameter in the handoff cost framework on the handoff cost components. We also compare the handoff performance of IPv6-based mobility protocols to the VMD. · We present a handoff cost optimization problem and analysis of its characteristics. We consider a mobility user as the primary focus of our study. We then identify the suitable mathematical methods that can be leveraged to solve the problem. We model the handoff cost problem in an optimization tool. We also conduct a mobility study - best of our knowledge, first of its kind - on providing a guide for finding the number of handoffs in a typical VMD for any given user\u27s mobility model. Plugging the output of mobility study, we then conduct a numerical analysis to find out optimum VMD for a given user mobility model and check if the theoretical inferences are in agreement with the output of the optimization tool