Survey and Systematization of Secure Device Pairing

Secure Device Pairing (SDP) schemes have been developed to facilitate secure communications among smart devices, both personal mobile devices and Internet of Things (IoT) devices. Comparison and assessment of SDP schemes is troublesome, because each scheme makes different assumptions about out-of-band channels and adversary models, and are driven by their particular use-cases. A conceptual model that facilitates meaningful comparison among SDP schemes is missing. We provide such a model. In this article, we survey and analyze a wide range of SDP schemes that are described in the literature, including a number that have been adopted as standards. A system model and consistent terminology for SDP schemes are built on the foundation of this survey, which are then used to classify existing SDP schemes into a taxonomy that, for the first time, enables their meaningful comparison and analysis.The existing SDP schemes are analyzed using this model, revealing common systemic security weaknesses among the surveyed SDP schemes that should become priority areas for future SDP research, such as improving the integration of privacy requirements into the design of SDP schemes. Our results allow SDP scheme designers to create schemes that are more easily comparable with one another, and to assist the prevention of persisting the weaknesses common to the current generation of SDP schemes.Comment: 34 pages, 5 figures, 3 tables, accepted at IEEE Communications Surveys & Tutorials 2017 (Volume: PP, Issue: 99

Network Management and Control for mmWave Communications

Millimeter-wave (mmWave) is one of the key technologies that enables the next wireless generation. mmWave offers a much higher bandwidth than sub-6GHz communications which allows multi-gigabit-per-second rates. This also alleviates the scarcity of spectrum at lower frequencies, where most devices connect through sub-6GHz bands. However new techniques are necessary to overcome the challenges associated with such high frequencies. Most of these challenges come from the high spatial attenuation at the mmWave band, which requires new paradigms that differ from sub-6GHz communications. Most notably mmWave telecommunications are characterized by the need to be directional in order to extend the operational range. This is achieved by using electronically steerable antenna arrays, that focus the energy towards the desired direction by combining each antenna element constructively or destructively. Additionally, most of the energy comes from the Line Of Sight (LOS) component which gives mmWave a quasi-optical behaviour where signals can reflect off walls and still be used for communication. Some other challenges that directional communications bring are mobility tracking, blockages and misalignments due to device rotation. The IEEE 802.11ad amendment introduced wireless telecommunications in the unlicensed 60 GHz band. It is the first standard to address the limitations of mmWave. It does so by introducing new mechanisms at the Medium Access Control (MAC) and Physical (PHY) layers. It introduces multi-band operation, relay operation mode, hybrid channel access scheme, beam tracking and beam forming among others. In this thesis we present a series of works that aim to improve mmWave telecommunications. First we give an overview of the intrinsic challenges of mmWave telecommunications, by explaining the modifications to the MAC and PHY layers. This sets the base for the rest of the thesis. Then do a comprehensive study on how mmWave behaves with existing technologies, namely TCP. TCP is unable to distinguish losses caused by congestion or by transmission errors caused by channel degradation. Since mmWave is affected by blockages more than sub-6GHz technologies, we propose a set of parameters that improve the channel quality even for mobile scenarios. The next job focuses on reducing the initial access overhead of mmWave by using sub-6GHz information to steer towards the desired direction. We start this work by doing a comprehensive High Frequency (HF) and Low Frequency (LF) correlation, analyzing the similarity of the existing paths between the two selected frequencies. Then we propose a beam steering algorithm that reduces the overhead to one third of the original time. Once we have studied how to reduce the initial access overhead, we propose a mechanism to reduce the beam tracking overhead. For this we propose an open platform based on a Field Programmable Gate Arrays (FPGA) where we implement an algorithm that completely removes the need to train on the Station (STA) side. This is achieved by changing beam patterns on the STA side while the Access Point (AP) is sending the preamble. We can change up to 10 beam patterns without losing connection and we reduce the overhead by a factor of 8.8 with respect to the IEEE 802.11ad standard. Finally we present a dual band location system based on Commercial-Off-The-Shelve (COTS) devices. Locating the STA can improve the quality of the channel significantly, since the AP can predict and react to possible blockages. First we reverse engineer existing 60 GHz enabled COTS devices to extract Channel State Information (CSI) and Fine Timing Measurements (FTM) measurements, from which we can estimate angle and distance. Then we develop an algorithm that is able to choose between HF and LF in order to improve the overall accuracy of the system. We achieve less than 17 cm of median error in indoor environments, even when some areas are Non Line Of Sight (NLOS).This work has been supported by IMDEA Networks Institute.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Matthias Hollick.- Secretario: Vincenzo Mancuso.- Vocal: Paolo Casar

Improving Location Accuracy And Network Capacity In Mobile Networks

Todays mobile computing must support a wide variety of applications such as location-based services, navigation, HD media streaming and augmented reality. Providing such services requires large network bandwidth and precise localization mechanisms, which face significant challenges. First, new (real-time) localization mechanisms are needed to locate neighboring devices/objects with high accuracy under tight environment constraints, e.g. without infrastructure support. Second, mobile networks need to deliver orders of magnitude more bandwidth to support the exponentially increasing traffic demand, and adapt resource usage to user mobility.In this dissertation, we build effective and practical solutions to address these challenges. Our first research area is to develop new localization mechanisms that utilize the rich set of sensors on smartphones to implement accurate localization systems. We propose two designs. The first system tracks distance to nearby devices with centimeter accuracy by transmitting acoustic signals between the devices. We design robust and efficient signal processing algorithms that measure distances accurately on the fly, thus enabling real-time user motion tracking. Our second system locates a transmitting device in real-time using commodity smart- phones. Driving by the insight that rotating a wireless receiver (smartphone) around a users body can effectively emulate the sensitivity and functionality of a directional antenna, we design a rotation-based measurement algorithm that can accurately predict the direction of the target transmitter and locate the transmitter with a few measurements.Our second research area is to develop next generation mobile networks to significantly boost network capacity. We propose a drastically new outdoor picocell design that leverages millimeter wave 60GHz transmissions to provide multi-Gbps bandwidth for mobile users. Using extensive measurements on off-the-shelf 60GHz radios, we explore the feasibility of 60GHz picocells by characterizing range, attenuation due to reflections, sensitivity to movement and blockage, and interference in typical urban environments. Our results dispel some common myths on 60GHz, and show that 60GHz outdoor picocells are indeed a feasible approach for delivering orders of magnitude increase in network capacity.Finally, we seek to capture and understand user mobility patterns which are essential in mobile network design and deployment. While traditional methods of collecting human mobility traces are expensive and not scalable, we explore a new direction that extracts large-scale mobility traces through widely available geosocial datasets, e.g. Foursquare "check-in" datasets. By comparing raw GPS traces against Foursquare checkins, we analyze the value of using geosocial datasets as representative traces of human mobility. We then develop techniques to both "sanitize" and "repopulate" geosocial traces, thus producing detailed mobility traces more indicative of actual human movement and suitable for mobile network design

Millimeter wave wearable communication networks : analytic modeling and MIMO support

Future high-end wearable electronic devices including virtual reality goggles and augmented reality glasses require rates of the order of gigabits-per-second and potentially very low latency. Supporting high data rate wireless connectivity for applications such as uncompressed video streaming among wearable devices in a densely crowded environment is challenging. This is primarily due to bandwidth scarcity when many users operate multiple devices simultaneously. The millimeter wave (mmWave) band has the potential to address this bottleneck, thanks to more spectrum and less interference because of signal blockage at these frequencies. This dissertation addresses key questions that need to be answered before realizing mmWave-based wearables in practice: (i) what are the expected achievable rates in a crowded user environment, with mmWave devices using a given hardware configuration? (ii) how is the wireless connectivity affected in an indoor operation, which is prone to surface reflections? (iii) can multi-stream data transmission, involving large bandwidth communication under hardware constraints be realized? To answer these, tools from stochastic geometry and compressive sensing, and architectures involving hybrid analog/digital multiple-input multiple-output (MIMO) are leveraged. The main contributions of this dissertation are 1) analytical modeling to compute average achievable rates in mmWave wearable networks consisting of finite number of user devices and human blockages, 2) characterizing the impact of reflections and non-isotropic performance of mmWave wearable networks in crowded indoor environments, 3) channel estimation to support MIMO for wideband mmWave wearable devices using hybrid architecture, and 4) designing optimal, but easy-to-implement, precoding/combining strategies in frequency-selective mmWave systems. Both analysis and numerical simulations show how the proposed evaluation methodology and solutions serve to enable mmWave based communication among next generation wearable electronic devices.Electrical and Computer Engineerin

A Test Environment for Wireless Hacking in Domestic IoT Scenarios

Security is gaining importance in the daily life of every citizen. The advent of Internet of Things devices in our lives is changing our conception of being connected through a single device to a multiple connection in which the centre of connection is becoming the devices themselves. This conveys the attack vector for a potential attacker is exponentially increased. This paper presents how the concatenation of several attacks on communication protocols (WiFi, Bluetooth LE, GPS, 433 Mhz and NFC) can lead to undesired situations in a domestic environment. A comprehensive analysis of the protocols with the identification of their weaknesses is provided. Some relevant aspects of the whole attacking procedure have been presented to provide some relevant tips and countermeasures.This work has been partially supported by the Spanish Ministry of Science and Innovation through the SecureEDGE project (PID2019-110565RB-I00), and by the by the Andalusian FEDER 2014-2020 Program through the SAVE project (PY18-3724). // Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. // Funding for open access charge: Universidad de Málaga / CBU

Wireless Positioning and Tracking for Internet of Things in GPS-denied Environments

Wireless positioning and tracking have long been a critical technology for various applications such as indoor/outdoor navigation, surveillance, tracking of assets and employees, and guided tours, among others. Proliferation of Internet of Things (IoT) devices, the evolution of smart cities, and vulnerabilities of traditional localization technologies to cyber-attacks such as jamming and spoofing of GPS necessitate development of novel radio frequency (RF) localization and tracking technologies that are accurate, energy-efficient, robust, scalable, non-invasive and secure. The main challenges that are considered in this research work are obtaining fundamental limits of localization accuracy using received signal strength (RSS) information with directional antennas, and use of burst and intermittent measurements for localization. In this dissertation, we consider various RSS-based techniques that rely on existing wireless infrastructures to obtain location information of corresponding IoT devices. In the first approach, we present a detailed study on localization accuracy of UHF RF IDentification (RFID) systems considering realistic radiation pattern of directional antennas. Radiation patterns of antennas and antenna arrays may significantly affect RSS in wireless networks. The sensitivity of tag antennas and receiver antennas play a crucial role. In this research, we obtain the fundamental limits of localization accuracy considering radiation patterns and sensitivity of the antennas by deriving Cramer-Rao Lower Bounds (CRLBs) using estimation theory techniques. In the second approach, we consider a millimeter Wave (mmWave) system with linear antenna array using beamforming radiation patterns to localize user equipment in an indoor environment. In the third approach, we introduce a tracking and occupancy monitoring system that uses ambient, bursty, and intermittent WiFi probe requests radiated from mobile devices. Burst and intermittent signals are prominent characteristics of IoT devices; using these features, we propose a tracking technique that uses interacting multiple models (IMM) with Kalman filtering. Finally, we tackle the problem of indoor UAV navigation to a wireless source using its Rayleigh fading RSS measurements. We propose a UAV navigation technique based on Q-learning that is a model-free reinforcement learning technique to tackle the variation in the RSS caused by Rayleigh fading