Self-Synchronization in Duty-cycled Internet of Things (IoT) Applications

In recent years, the networks of low-power devices have gained popularity. Typically these devices are wireless and interact to form large networks such as the Machine to Machine (M2M) networks, Internet of Things (IoT), Wearable Computing, and Wireless Sensor Networks. The collaboration among these devices is a key to achieving the full potential of these networks. A major problem in this field is to guarantee robust communication between elements while keeping the whole network energy efficient. In this paper, we introduce an extended and improved emergent broadcast slot (EBS) scheme, which facilitates collaboration for robust communication and is energy efficient. In the EBS, nodes communication unit remains in sleeping mode and are awake just to communicate. The EBS scheme is fully decentralized, that is, nodes coordinate their wake-up window in partially overlapped manner within each duty-cycle to avoid message collisions. We show the theoretical convergence behavior of the scheme, which is confirmed through real test-bed experimentation.Comment: 12 Pages, 11 Figures, Journa

Timescales of Massive Human Entrainment

The past two decades have seen an upsurge of interest in the collective behaviors of complex systems composed of many agents entrained to each other and to external events. In this paper, we extend concepts of entrainment to the dynamics of human collective attention. We conducted a detailed investigation of the unfolding of human entrainment - as expressed by the content and patterns of hundreds of thousands of messages on Twitter - during the 2012 US presidential debates. By time locking these data sources, we quantify the impact of the unfolding debate on human attention. We show that collective social behavior covaries second-by-second to the interactional dynamics of the debates: A candidate speaking induces rapid increases in mentions of his name on social media and decreases in mentions of the other candidate. Moreover, interruptions by an interlocutor increase the attention received. We also highlight a distinct time scale for the impact of salient moments in the debate: Mentions in social media start within 5-10 seconds after the moment; peak at approximately one minute; and slowly decay in a consistent fashion across well-known events during the debates. Finally, we show that public attention after an initial burst slowly decays through the course of the debates. Thus we demonstrate that large-scale human entrainment may hold across a number of distinct scales, in an exquisitely time-locked fashion. The methods and results pave the way for careful study of the dynamics and mechanisms of large-scale human entrainment.Comment: 20 pages, 7 figures, 6 tables, 4 supplementary figures. 2nd version revised according to peer reviewers' comments: more detailed explanation of the methods, and grounding of the hypothese

Modélisation formelle des systèmes de détection d'intrusions

L’écosystème de la cybersécurité évolue en permanence en termes du nombre, de la diversité, et de la complexité des attaques. De ce fait, les outils de détection deviennent inefficaces face à certaines attaques. On distingue généralement trois types de systèmes de détection d’intrusions : détection par anomalies, détection par signatures et détection hybride. La détection par anomalies est fondée sur la caractérisation du comportement habituel du système, typiquement de manière statistique. Elle permet de détecter des attaques connues ou inconnues, mais génère aussi un très grand nombre de faux positifs. La détection par signatures permet de détecter des attaques connues en définissant des règles qui décrivent le comportement connu d’un attaquant. Cela demande une bonne connaissance du comportement de l’attaquant. La détection hybride repose sur plusieurs méthodes de détection incluant celles sus-citées. Elle présente l’avantage d’être plus précise pendant la détection. Des outils tels que Snort et Zeek offrent des langages de bas niveau pour l’expression de règles de reconnaissance d’attaques. Le nombre d’attaques potentielles étant très grand, ces bases de règles deviennent rapidement difficiles à gérer et à maintenir. De plus, l’expression de règles avec état dit stateful est particulièrement ardue pour reconnaître une séquence d’événements. Dans cette thèse, nous proposons une approche stateful basée sur les diagrammes d’état-transition algébriques (ASTDs) afin d’identifier des attaques complexes. Les ASTDs permettent de représenter de façon graphique et modulaire une spécification, ce qui facilite la maintenance et la compréhension des règles. Nous étendons la notation ASTD avec de nouvelles fonctionnalités pour représenter des attaques complexes. Ensuite, nous spécifions plusieurs attaques avec la notation étendue et exécutons les spécifications obtenues sur des flots d’événements à l’aide d’un interpréteur pour identifier des attaques. Nous évaluons aussi les performances de l’interpréteur avec des outils industriels tels que Snort et Zeek. Puis, nous réalisons un compilateur afin de générer du code exécutable à partir d’une spécification ASTD, capable d’identifier de façon efficiente les séquences d’événements.Abstract : The cybersecurity ecosystem continuously evolves with the number, the diversity, and the complexity of cyber attacks. Generally, we have three types of Intrusion Detection System (IDS) : anomaly-based detection, signature-based detection, and hybrid detection. Anomaly detection is based on the usual behavior description of the system, typically in a static manner. It enables detecting known or unknown attacks but also generating a large number of false positives. Signature based detection enables detecting known attacks by defining rules that describe known attacker’s behavior. It needs a good knowledge of attacker behavior. Hybrid detection relies on several detection methods including the previous ones. It has the advantage of being more precise during detection. Tools like Snort and Zeek offer low level languages to represent rules for detecting attacks. The number of potential attacks being large, these rule bases become quickly hard to manage and maintain. Moreover, the representation of stateful rules to recognize a sequence of events is particularly arduous. In this thesis, we propose a stateful approach based on algebraic state-transition diagrams (ASTDs) to identify complex attacks. ASTDs allow a graphical and modular representation of a specification, that facilitates maintenance and understanding of rules. We extend the ASTD notation with new features to represent complex attacks. Next, we specify several attacks with the extended notation and run the resulting specifications on event streams using an interpreter to identify attacks. We also evaluate the performance of the interpreter with industrial tools such as Snort and Zeek. Then, we build a compiler in order to generate executable code from an ASTD specification, able to efficiently identify sequences of events

Time synchronization in wireless sensor networks

Time synchronization is basic requirements for various applications in wireless sensor network, e.g., event detection, speed estimating, environment monitoring, data aggregation, target tracking, scheduling and sensor nodes cooperation. Time synchronization is also helpful to save energy in WSN because it provides the possibility to set nodes into the sleeping mode. In wireless sensor networks all of above applications need that all sensor nodes have a common time reference. However, most existing time synchronization protocols are likely to deteriorate or even be destroyed when the WSNs attack by malicious intruders. The recently developed maximum and minimum consensus based time synchronization protocol (MMTS) is a promising alternative as it does not depend on any reference node or network topology. But MMTS is vulnerable to message manipulation attacks. In this thesis, we focus on how to defend the MMTS protocol in wireless sensor networks under message manipulation attacks. We investigate the impact of message manipulation attacks over MMTS. Then, a Secured Maximum and Minimum Consensus based Time Synchronization (SMMTS) protocol is proposed to detect and invalidate message manipulation attacks

Building Evacuation with Mobile Devices

In der Dissertation wird ein Konzept für ein Gebäudeevakuierungssystem vorgestellt, das es ermöglicht, Personen mit Hilfe mobiler Endgeräte im Evakuierungsfall aus einem Gebäude zu führen. Die Dissertation gliedert sich in drei thematische Bereiche, in denen zunächst ein Konzept für die Systemarchitektur vorgestellt wird und anschließend verschiedene Algorithmen zur Routenplanung sowie zur Lokalisierung der Geräte vorgestellt und evaluiert werden

Multichannel Distributed Coordination for Wireless Sensor Networks: Convergence Delay and Energy Consumption Aspects

This thesis develops new approaches for distributed coordination of data-intensive communications between wireless sensor nodes. In particular, the topic of synchronization, and its dual primitive, desynchronization at the Medium Access Control (MAC) or the Application (APP) layer of the OSI stack, is studied in detail. In Chapters 1 and 2, the related literature on the problem of synchronization is overviewed and the main approaches for distributed (de)synchronization at the MAC or APP layers are analyzed, designed and implemented on IEEE802.15.4- enabled wireless sensor nodes. Beyond the experimental validation of distributed (de)synchronization approaches, the three main contributions of this thesis, corresponding to the related publications found below, are: • establishing for the first time the expected time for convergence to distributed time division multiple access (TDMA) operation under the two main desynchronization models proposed in the literature and validating the derived estimates via a real-world implementation (Chapter 3); • proposing the extension of the main desynchronization models towards multi-hop and multi-channel operation; the latter is achieved by extending the concept of reactive listening to multi-frequency operation (Chapter 4 and 5). • analyzing the energy consumption of the distributed TDMA approach under different transmission probability density functions (Chapter 6 and 7). Conclusions and items for future work in relation to the proposals of this thesis are described in Chapter 8

A Wireless Sensor Data Fusion Framework for Contaminant Detection

In the search for more effective instruments to collect data for the identification of threats to security, health, and safety, new tools must be designed to meet the challenges of a diverse set of possible applications. The extensive range of potential applications raises the need for a general purpose system capable of addressing a wide variety of deployment environments. This thesis focuses on a wireless sensor network framework for collecting environmental data in an effort to develop a sensing solution that fits within many design spaces. The framework includes reconfigurable wireless sensor node hardware, firmware, and software for interfacing sensor networks for upstream data aggregation and sensor data fusion. The wireless sensor modules utilize mesh network architecture to allow low power radios to be effective even with low sensor module dispersion density, or in environments that have obstructions which prevent line-of-sight communications. In the current implementation, the software is designed to allow a computer to be used to monitor all sensor module activities as data is collected, request information as needed, and forward collected data to a database system for further analysis. It also supports software modules to allow different sensor data fusion and analysis algorithms to be applied to the collected data in real-time

Techniques for Decentralized and Dynamic Resource Allocation

abstract: This thesis investigates three different resource allocation problems, aiming to achieve two common goals: i) adaptivity to a fast-changing environment, ii) distribution of the computation tasks to achieve a favorable solution. The motivation for this work relies on the modern-era proliferation of sensors and devices, in the Data Acquisition Systems (DAS) layer of the Internet of Things (IoT) architecture. To avoid congestion and enable low-latency services, limits have to be imposed on the amount of decisions that can be centralized (i.e. solved in the ``cloud") and/or amount of control information that devices can exchange. This has been the motivation to develop i) a lightweight PHY Layer protocol for time synchronization and scheduling in Wireless Sensor Networks (WSNs), ii) an adaptive receiver that enables Sub-Nyquist sampling, for efficient spectrum sensing at high frequencies, and iii) an SDN-scheme for resource-sharing across different technologies and operators, to harmoniously and holistically respond to fluctuations in demands at the eNodeB' s layer. The proposed solution for time synchronization and scheduling is a new protocol, called PulseSS, which is completely event-driven and is inspired by biological networks. The results on convergence and accuracy for locally connected networks, presented in this thesis, constitute the theoretical foundation for the protocol in terms of performance guarantee. The derived limits provided guidelines for ad-hoc solutions in the actual implementation of the protocol. The proposed receiver for Compressive Spectrum Sensing (CSS) aims at tackling the noise folding phenomenon, e.g., the accumulation of noise from different sub-bands that are folded, prior to sampling and baseband processing, when an analog front-end aliasing mixer is utilized. The sensing phase design has been conducted via a utility maximization approach, thus the scheme derived has been called Cognitive Utility Maximization Multiple Access (CUMMA). The framework described in the last part of the thesis is inspired by stochastic network optimization tools and dynamics. While convergence of the proposed approach remains an open problem, the numerical results here presented suggest the capability of the algorithm to handle traffic fluctuations across operators, while respecting different time and economic constraints. The scheme has been named Decomposition of Infrastructure-based Dynamic Resource Allocation (DIDRA).Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201