Threats and perspective for the Internet of Things

Il paradigma di ubiquitous computing sta lentamente entrando nella vita di tutti i giorni, gli utenti sono sempre connessi e una nuova esigenza di monitoraggio e controllo sta nascendo. Dispositivi di comunicazione intelligenti, le reti domestiche multimediali e l’automazione industriale sono alcune coniugazioni possibili del paradigma di ubiquitous computing che sono ora disponibili per l’utente finale. La diffusione di questi sistemi è infatti destinata a crescere, spinta da entrambi i mondi accademico e industriale la quantità di lavoro di ricerca in questo campo è in aumento, e diverse aziende hanno messo le proprie soluzioni sul mercato. Nella visione di molti, l’utente sarebbe poi in grado di godere dei vantaggi di un sistema intelligente e impercettibile che si adatta all’ambiente ed ai suoi bisogni e unisce tutte le applicazioni e i servizi in un unico sistema integrato e facile da controllare. In questo lavoro vengono valutate alcune delle sfide architettoniche di questo nuovo modo di interagire tra l’utente e il suo ambiente circostante. Vengono mostrate la progettazione e la realizzazione di un SIP-based Home Gateway per il controllo remoto di Smart Objects in un ambiente domotico. È presentata anche un’architettura basata sul protocollo SIP per realizzare un sistema di domotica capace di interagire con dispositivi eterogenei e con varie interfacce utente, l’architettura si basa sull’uso del protocollo SIP come piano di controllo comune ed è centrata sul SIP Gateway Home. Per valutare le capacità del sistema descritto abbiamo effettuato anche una valutazione delle prestazioni, considerando i due problemi principali per questo tipo di dispositivi: scalabilita ad un elevato numero di richieste di servizio per secondo e l’interferenza/coesistenza di dispositivi appartenenti a diverse tecnologie/standard (ZigBee, Bluetooth, e Wi-Fi) presenti sullo stesso dispositivo. Sono stati valutati anche i problemi di sicurezza attraverso lo studio sperimentale di un Intrusion Detection System per attenuare tali problemi

Security techniques for sensor systems and the Internet of Things

Sensor systems are becoming pervasive in many domains, and are recently being generalized by the Internet of Things (IoT). This wide deployment, however, presents significant security issues. We develop security techniques for sensor systems and IoT, addressing all security management phases. Prior to deployment, the nodes need to be hardened. We develop nesCheck, a novel approach that combines static analysis and dynamic checking to efficiently enforce memory safety on TinyOS applications. As security guarantees come at a cost, determining which resources to protect becomes important. Our solution, OptAll, leverages game-theoretic techniques to determine the optimal allocation of security resources in IoT networks, taking into account fixed and variable costs, criticality of different portions of the network, and risk metrics related to a specified security goal. Monitoring IoT devices and sensors during operation is necessary to detect incidents. We design Kalis, a knowledge-driven intrusion detection technique for IoT that does not target a single protocol or application, and adapts the detection strategy to the network features. As the scale of IoT makes the devices good targets for botnets, we design Heimdall, a whitelist-based anomaly detection technique for detecting and protecting against IoT-based denial of service attacks. Once our monitoring tools detect an attack, determining its actual cause is crucial to an effective reaction. We design a fine-grained analysis tool for sensor networks that leverages resident packet parameters to determine whether a packet loss attack is node- or link-related and, in the second case, locate the attack source. Moreover, we design a statistical model for determining optimal system thresholds by exploiting packet parameters variances. With our techniques\u27 diagnosis information, we develop Kinesis, a security incident response system for sensor networks designed to recover from attacks without significant interruption, dynamically selecting response actions while being lightweight in communication and energy overhead

Correct-by-Construction Development of Dynamic Topology Control Algorithms

Wireless devices are influencing our everyday lives today and will even more so in the future. A wireless sensor network (WSN) consists of dozens to hundreds of small, cheap, battery-powered, resource-constrained sensor devices (motes) that cooperate to serve a common purpose. These networks are applied in safety- and security-critical areas (e.g., e-health, intrusion detection). The topology of such a system is an attributed graph consisting of nodes representing the devices and edges representing the communication links between devices. Topology control (TC) improves the energy consumption behavior of a WSN by blocking costly links. This allows a mote to reduce its transmission power. A TC algorithm must fulfill important consistency properties (e.g., that the resulting topology is connected). The traditional development process for TC algorithms only considers consistency properties during the initial specification phase. The actual implementation is carried out manually, which is error prone and time consuming. Thus, it is difficult to verify that the implementation fulfills the required consistency properties. The problem becomes even more severe if the development process is iterative. Additionally, many TC algorithms are batch algorithms, which process the entire topology, irrespective of the extent of the topology modifications since the last execution. Therefore, dynamic TC is desirable, which reacts to change events of the topology. In this thesis, we propose a model-driven correct-by-construction methodology for developing dynamic TC algorithms. We model local consistency properties using graph constraints and global consistency properties using second-order logic. Graph transformation rules capture the different types of topology modifications. To specify the control flow of a TC algorithm, we employ the programmed graph transformation language story-driven modeling. We presume that local consistency properties jointly imply the global consistency properties. We ensure the fulfillment of the local consistency properties by synthesizing weakest preconditions for each rule. The synthesized preconditions prohibit the application of a rule if and only if the application would lead to a violation of a consistency property. Still, this restriction is infeasible for topology modifications that need to be executed in any case. Therefore, as a major contribution of this thesis, we propose the anticipation loop synthesis algorithm, which transforms the synthesized preconditions into routines that anticipate all violations of these preconditions. This algorithm also enables the correct-by-construction runtime reconfiguration of adaptive WSNs. We provide tooling for both common evaluation steps. Cobolt allows to evaluate the specified TC algorithms rapidly using the network simulator Simonstrator. cMoflon generates embedded C code for hardware testbeds that build on the sensor operating system Contiki

Community Sense and Response Systems

The proliferation of smartphones and other internet-enabled, sensor-equipped consumer devices enables us to sense and act upon the physical environment in unprecedented ways. This thesis considers Community Sense-and-Response (CSR) systems, a new class of web application for acting on sensory data gathered from participants' personal smart devices. The thesis describes how rare events can be reliably detected using a decentralized anomaly detection architecture that performs client-side anomaly detection and server-side event detection. After analyzing this decentralized anomaly detection approach, the thesis describes how weak but spatially structured events can be detected, despite significant noise, when the events have a sparse representation in an alternative basis. Finally, the thesis describes how the statistical models needed for client-side anomaly detection may be learned efficiently, using limited space, via coresets. The Caltech Community Seismic Network (CSN) is a prototypical example of a CSR system that harnesses accelerometers in volunteers' smartphones and consumer electronics. Using CSN, this thesis presents the systems and algorithmic techniques to design, build and evaluate a scalable network for real-time awareness of spatial phenomena such as dangerous earthquakes.</p