210 research outputs found

    Cognitive privacy for personal clouds

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    This paper proposes a novel Cognitive Privacy (CogPriv) framework that improves privacy of data sharing between Personal Clouds for different application types and across heterogeneous networks. Depending on the behaviour of neighbouring network nodes, their estimated privacy levels, resource availability, and social network connectivity, each Personal Cloud may decide to use different transmission network for different types of data and privacy requirements. CogPriv is fully distributed, uses complex graph contacts analytics and multiple implicit novel heuristics, and combines these with smart probing to identify presence and behaviour of privacy compromising nodes in the network. Based on sensed local context and through cooperation with remote nodes in the network, CogPriv is able to transparently and on-the-fly change the network in order to avoid transmissions when privacy may be compromised. We show that CogPriv achieves higher end-to-end privacy levels compared to both noncognitive cellular network communication and state-of-the-art strategies based on privacy-aware adaptive social mobile networks routing for a range of experiment scenarios based on real-world user and network traces. CogPriv is able to adapt to varying network connectivity and maintain high quality of service while managing to keep low data exposure for a wide range of privacy leakage levels in the infrastructure

    Advancement in infotainment system in automotive sector with vehicular cloud network and current state of art

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    The automotive industry has been incorporating various technological advancement on top-end versions of the vehicle order to improvise the degree of comfortability as well as enhancing the safer driving system. Infotainment system is one such pivotal system which not only makes the vehicle smart but also offers abundance of information as well as entertainment to the driver and passenger. The capability to offer extensive relay of service through infotainment system is highly dependent on vehicular adhoc network as well as back end support of cloud environment. However, it is know that such legacy system of vehicular adhoc network is also characterized by various problems associated with channel capacity, latency, heterogeneous network processing, and many more. Therefore, this paper offers a comprehensive insight to the research work being carried out towards leveraging the infotainment system in order to obtain the true picture of strength, limitation, and open end problems associated with infotainment system

    IFHNFS: fast indexing information in mobile devices

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    Abstract To track movements of objects and people we need to use expensive technologies and complex softwares. Usually these softwares need lots of memory. There are many examples of objects and people of which would be useful to know the precise locations. Something sent via pony express, position of buses in the city, friends' locations, and so on. Our purpose is to use connectivity of smartphone to share position via gps by using only a filesystem created ad hoc without databases or user space programs. IFHNFS is based on Hixosfs and NFS (Linux kernel). Indexing the most relevant data directly in the fs structure makes the exchange of data Faster and, via NFS, potentially available whenever and whenever. Ad-hoc solutions for Android have been developed in real contexts. The system have been tested on a network of Android OS devices that share data with a Linux server

    Interference charecterisation, location and bandwidth estimation in emerging WiFi networks

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    Wireless LAN technology based on the IEEE 802.11 standard, commonly referred to as WiFi, has been hugely successful not only for the last hop access to the Internet in home, office and hotspot scenarios but also for realising wireless backhaul in mesh networks and for point -to -point long- distance wireless communication. This success can be mainly attributed to two reasons: low cost of 802.11 hardware from reaching economies of scale, and operation in the unlicensed bands of wireless spectrum.The popularity of WiFi, in particular for indoor wireless access at homes and offices, has led to significant amount of research effort looking at the performance issues arising from various factors, including interference, CSMA/CA based MAC protocol used by 802.11 devices, the impact of link and physical layer overheads on application performance, and spatio-temporal channel variations. These factors affect the performance of applications and services that run over WiFi networks. In this thesis, we experimentally investigate the effects of some of the above mentioned factors in the context of emerging WiFi network scenarios such as multi- interface indoor mesh networks, 802.11n -based WiFi networks and WiFi networks with virtual access points (VAPs). More specifically, this thesis comprises of four experimental characterisation studies: (i) measure prevalence and severity of co- channel interference in urban WiFi deployments; (ii) characterise interference in multi- interface indoor mesh networks; (iii) study the effect of spatio-temporal channel variations, VAPs and multi -band operation on WiFi fingerprinting based location estimation; and (iv) study the effects of newly introduced features in 802.11n like frame aggregation (FA) on available bandwidth estimation.With growing density of WiFi deployments especially in urban areas, co- channel interference becomes a major factor that adversely affects network performance. To characterise the nature of this phenomena at a city scale, we propose using a new measurement methodology called mobile crowdsensing. The idea is to leverage commodity smartphones and the natural mobility of people to characterise urban WiFi co- channel interference. Specifically, we report measurement results obtained for Edinburgh, a representative European city, on detecting the presence of deployed WiFi APs via the mobile crowdsensing approach. These show that few channels in 2.4GHz are heavily used and there is hardly any activity in the 5GHz band even though relatively it has a greater number of available channels. Spatial analysis of spectrum usage reveals that co- channel interference among nearby APs operating in the same channel can be a serious problem with around 10 APs contending with each other in many locations. We find that the characteristics of WiFi deployments at city -scale are similar to those of WiFi deployments in public spaces of different indoor environments. We validate our approach in comparison with wardriving, and also show that our findings generally match with previous studies based on other measurement approaches. As an application of the mobile crowdsensing based urban WiFi monitoring, we outline a cloud based WiFi router configuration service for better interference management with global awareness in urban areas.For mesh networks, the use of multiple radio interfaces is widely seen as a practical way to achieve high end -to -end network performance and better utilisation of available spectrum. However this gives rise to another type of interference (referred to as coexistence interference) due to co- location of multiple radio interfaces. We show that such interference can be so severe that it prevents concurrent successful operation of collocated interfaces even when they use channels from widely different frequency bands. We propose the use of antenna polarisation to mitigate such interference and experimentally study its benefits in both multi -band and single -band configurations. In particular, we show that using differently polarised antennas on a multi -radio platform can be a helpful counteracting mechanism for alleviating receiver blocking and adjacent channel interference phenomena that underlie multi -radio coexistence interference. We also validate observations about adjacent channel interference from previous studies via direct and microscopic observation of MAC behaviour.Location is an indispensable information for navigation and sensing applications. The rapidly growing adoption of smartphones has resulted in a plethora of mobile applications that rely on position information (e.g., shopping apps that use user position information to recommend products to users and help them to find what they want in the store). WiFi fingerprinting is a popular and well studied approach for indoor location estimation that leverages the existing WiFi infrastructure and works based on the difference in strengths of the received AP signals at different locations. However, understanding the impact of WiFi network deployment aspects such as multi -band APs and VAPs has not received much attention in the literature. We first examine the impact of various aspects underlying a WiFi fingerprinting system. Specifically, we investigate different definitions for fingerprinting and location estimation algorithms across different indoor environments ranging from a multi- storey office building to shopping centres of different sizes. Our results show that the fingerprint definition is as important as the choice of location estimation algorithm and there is no single combination of these two that works across all environments or even all floors of a given environment. We then consider the effect of WiFi frequency bands (e.g., 2.4GHz and 5GHz) and the presence of virtual access points (VAPs) on location accuracy with WiFi fingerprinting. Our results demonstrate that lower co- channel interference in the 5GHz band yields more accurate location estimation. We show that the inclusion of VAPs has a significant impact on the location accuracy of WiFi fingerprinting systems; we analyse the potential reasons to explain the findings.End -to -end available bandwidth estimation (ABE) has a wide range of uses, from adaptive application content delivery, transport-level transmission rate adaptation and admission control to traffic engineering and peer node selection in peer -to- peer /overlay networks [ 1, 2]. Given its importance, it has been received much research attention in both wired data networks and legacy WiFi networks (based on 802.11 a/b /g standards), resulting in different ABE techniques and tools proposed to optimise different criteria and suit different scenarios. However, effects of new MAC/PHY layer enhancements in new and next generation WiFi networks (based on 802.11n and 802.11ac standards) have not been studied yet. We experimentally find that among different new features like frame aggregation, channel bonding and MIMO modes (spacial division multiplexing), frame aggregation has the most harmful effect as it has direct effect on ABE by distorting the measurement probing traffic pattern commonly used to estimate available bandwidth. Frame aggregation is also specified in both 802.11n and 802.1 lac standards as a mandatory feature to be supported. We study the effect of enabling frame aggregation, for the first time, on the performance of the ABE using an indoor 802.11n wireless testbed. The analysis of results obtained using three tools - representing two main Probe Rate Model (PRM) and Probe Gap Model (PGM) based approaches for ABE - led us to come up with the two key principles of jumbo probes and having longer measurement probe train sizes to counter the effects of aggregating frames on the performance of ABE tools. Then, we develop a new tool, WBest+ that is aware of the underlying frame aggregation by incorporating these principles. The experimental evaluation of WBest+ shows more accurate ABE in the presence of frame aggregation.Overall, the contributions of this thesis fall in three categories - experimental characterisation, measurement techniques and mitigation/solution approaches for performance problems in emerging WiFi network scenarios. The influence of various factors mentioned above are all studied via experimental evaluation in a testbed or real - world setting. Specifically, co- existence interference characterisation and evaluation of available bandwidth techniques are done using indoor testbeds, whereas characterisation of urban WiFi networks and WiFi fingerprinting based location estimation are carried out in real environments. New measurement approaches are also introduced to aid better experimental evaluation or proposed as new measurement tools. These include mobile crowdsensing based WiFi monitoring; MAC/PHY layer monitoring of co- existence interference; and WBest+ tool for available bandwidth estimation. Finally, new mitigation approaches are proposed to address challenges and problems identified throughout the characterisation studies. These include: a proposal for crowd - based interference management in large scale uncoordinated WiFi networks; exploiting antenna polarisation diversity to remedy the effects of co- existence interference in multi -interface platforms; taking advantage of VAPs and multi -band operation for better location estimation; and introducing the jumbo frame concept and longer probe train sizes to improve performance of ABE tools in next generation WiFi networks

    Universal Mobile Service Execution Framework for Device-To-Device Collaborations

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    There are high demands of effective and high-performance of collaborations between mobile devices in the places where traditional Internet connections are unavailable, unreliable, or significantly overburdened, such as on a battlefield, disaster zones, isolated rural areas, or crowded public venues. To enable collaboration among the devices in opportunistic networks, code offloading and Remote Method Invocation are the two major mechanisms to ensure code portions of applications are successfully transmitted to and executed on the remote platforms. Although these domains are highly enjoyed in research for a decade, the limitations of multi-device connectivity, system error handling or cross platform compatibility prohibit these technologies from being broadly applied in the mobile industry. To address the above problems, we designed and developed UMSEF - an Universal Mobile Service Execution Framework, which is an innovative and radical approach for mobile computing in opportunistic networks. Our solution is built as a component-based mobile middleware architecture that is flexible and adaptive with multiple network topologies, tolerant for network errors and compatible for multiple platforms. We provided an effective algorithm to estimate the resource availability of a device for higher performance and energy consumption and a novel platform for mobile remote method invocation based on declarative annotations over multi-group device networks. The experiments in reality exposes our approach not only achieve the better performance and energy consumption, but can be extended to large-scaled ubiquitous or IoT systems

    Secure Communication in Disaster Scenarios

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    WĂ€hrend Naturkatastrophen oder terroristischer AnschlĂ€ge ist die bestehende Kommunikationsinfrastruktur hĂ€ufig ĂŒberlastet oder fĂ€llt komplett aus. In diesen Situationen können mobile GerĂ€te mithilfe von drahtloser ad-hoc- und unterbrechungstoleranter Vernetzung miteinander verbunden werden, um ein Notfall-Kommunikationssystem fĂŒr Zivilisten und Rettungsdienste einzurichten. Falls verfĂŒgbar, kann eine Verbindung zu Cloud-Diensten im Internet eine wertvolle Hilfe im Krisen- und Katastrophenmanagement sein. Solche Kommunikationssysteme bergen jedoch ernsthafte Sicherheitsrisiken, da Angreifer versuchen könnten, vertrauliche Daten zu stehlen, gefĂ€lschte Benachrichtigungen von Notfalldiensten einzuspeisen oder Denial-of-Service (DoS) Angriffe durchzufĂŒhren. Diese Dissertation schlĂ€gt neue AnsĂ€tze zur Kommunikation in Notfallnetzen von mobilen GerĂ€ten vor, die von der Kommunikation zwischen MobilfunkgerĂ€ten bis zu Cloud-Diensten auf Servern im Internet reichen. Durch die Nutzung dieser AnsĂ€tze werden die Sicherheit der GerĂ€te-zu-GerĂ€te-Kommunikation, die Sicherheit von Notfall-Apps auf mobilen GerĂ€ten und die Sicherheit von Server-Systemen fĂŒr Cloud-Dienste verbessert

    Supporting Large Scale Communication Systems on Infrastructureless Networks Composed of Commodity Mobile Devices: Practicality, Scalability, and Security.

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    Infrastructureless Delay Tolerant Networks (DTNs) composed of commodity mobile devices have the potential to support communication applications resistant to blocking and censorship, as well as certain types of surveillance. In this thesis we study the utility, practicality, robustness, and security of these networks. We collected two sets of wireless connectivity traces of commodity mobile devices with different granularity and scales. The first dataset is collected through active installation of measurement software on volunteer users' own smartphones, involving 111 users of a DTN microblogging application that we developed. The second dataset is collected through passive observation of WiFi association events on a university campus, involving 119,055 mobile devices. Simulation results show consistent message delivery performances of the two datasets. Using an epidemic flooding protocol, the large network achieves an average delivery rate of 0.71 in 24 hours and a median delivery delay of 10.9 hours. We show that this performance is appropriate for sharing information that is not time sensitive, e.g., blogs and photos. We also show that using an energy efficient variant of the epidemic flooding protocol, even the large network can support text messages while only consuming 13.7% of a typical smartphone battery in 14 hours. We found that the network delivery rate and delay are robust to denial-of-service and censorship attacks. Attacks that randomly remove 90% of the network participants only reduce delivery rates by less than 10%. Even when subjected to targeted attacks, the network suffered a less than 10% decrease in delivery rate when 40% of its participants were removed. Although structurally robust, the openness of the proposed network introduces numerous security concerns. The Sybil attack, in which a malicious node poses as many identities in order to gain disproportionate influence, is especially dangerous as it breaks the assumption underlying majority voting. Many defenses based on spatial variability of wireless channels exist, and we extend them to be practical for ad hoc networks of commodity 802.11 devices without mutual trust. We present the Mason test, which uses two efficient methods for separating valid channel measurement results of behaving nodes from those falsified by malicious participants.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120779/1/liuyue_1.pd

    Security in Internet of Things: networked smart objects.

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    Internet of Things (IoT) is an innovative paradigm approaching both industries and humans every-day life. It refers to the networked interconnection of every-day objects, which are equipped with ubiquitous intelligence. It not only aims at increasing the ubiquity of the Internet, but also at leading towards a highly distributed network of devices communicating with human beings as well as with other devices. Thanks to rapid advances in underlying technologies, IoT is opening valuable opportunities for a large number of novel applications, that promise to improve the quality of humans lives, facilitating the exchange of services. In this scenario, security represents a crucial aspect to be addressed, due to the high level of heterogeneity of the involved devices and to the sensibility of the managed information. Moreover, a system architecture should be established, before the IoT is fully operable in an efficient, scalable and interoperable manner. The main goal of this PhD thesis concerns the design and the implementation of a secure and distributed middleware platform tailored to IoT application domains. The effectiveness of the proposed solution is evaluated by means of a prototype and real case studies
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